[{"data":1,"prerenderedAt":1225},["ShallowReactive",2],{"method-chen1992pointtoplane":3},{"method":4,"reference":53,"equipment":72,"figures":89,"results":90},{"id":5,"label":6,"shortName":7,"title":8,"year":9,"era":10,"cluster":11,"scope":12,"keyIdeaZh":13,"keyIdeaEn":14,"fulltextStatus":15,"publicationStatus":16,"recommendation":17,"constructionRelevance":18,"validationEnvironment":19,"strengths":21,"limitations":26,"sensors":32,"platform":34,"estimator":36,"association":37,"timeModel":38,"deskew":39,"loopClosure":40,"globalOptimization":41,"mapRepresentation":42,"prior":43,"outputGeometry":44,"compute":45,"codeUrl":46,"codeLicense":47,"relatedVersions":48},"chen1992pointtoplane","Chen & Medioni, 1992","Point-to-plane ICP (Chen-Medioni)","Object modelling by registration of multiple range images",1992,"classic","C02","registration_component","此文為點對平面 ICP 的原始期刊版本。作者假設兩個視角已有近似配準，在 P 上以規則格點挑選平滑區域的控制點，沿 P 在該點的法向線與數位曲面 Q 求交（以切平面迭代近似，通常 3 至 5 次），再以 Q 在交點的切平面為目標，最小化控制點到切平面的有號距離平方和，不需要點對點對應。實驗以結構光測距儀取得莫札特半身像、牙齒模型與木塊的距離影像；多視角建模時把新視角對已合併的全部資料配準，以減少逐對配準的誤差累積。","Original journal version of point-to-plane ICP: control points in smooth regions of P are paired, via intersection of the P-normal line with surface Q, with the tangent plane of Q, and squared point-to-tangent-plane distances are minimized iteratively from an approximate initial pose; applied to multi-view range-image object modelling.","full_text_reviewed","peer_reviewed_published","main_body","not_reported",[20],"controlled_experiment",[22,23,24,25],"estimated rotations -15.06 deg (actual -15 deg) and -19.75 deg (actual -20 deg) (p. 152)","error histograms comparable to the data resolution: std 0.6523 mm (Mozart) and 0.3219 mm (tooth) (Figs. 5d, 6e)","points may slide within the tangent plane, so constraints from different control points are less conflicting and convergence is faster than with fixed control-point pairs (p. 148)","works on free-form objects with few detectable features (pp. 151-153)",[27,28,29,30,31],"an approximate initial transformation must be supplied (p. 153)","the cylindrical or spherical representation cannot directly handle more complex objects (p. 153)","no measure yet to ensure a good spatial distribution of control points (p. 150)","line-surface intersection fails when the projection falls outside Q or the normal is nearly perpendicular to the z axis (p. 149)","small uncovered areas remain near the poles of the spherical maps (p. 153)",[33],"structured-light range finder after Sato and Inokuchi: projector with a programmable liquid crystal mask and a CCD camera, space coding with projected stripe patterns and triangulation; accuracy about 1 mm; range images at 0.5 mm spatial resolution stored as 32-bit floats",[35],"rotary table (objects rotated on a turntable; object laid down for top and bottom views)","iterative least squares: at each iteration find T minimizing the sum of squared signed distances from transformed control points to the tangent planes of Q at the normal-line intersection points (Eq. 10), compose T^k = T T^(k-1), stop when the change measure of Eq. 11 falls below epsilon_c (0.01 in tests); cost per iteration linear in the number of control points","no point-to-point correspondence: for each control point p_i on P the line along the P-normal is intersected with digital surface Q by a Newton-like tangent-plane iteration (typically 3 to 5 iterations, stop within one sampling unit), and the tangent plane of Q at that intersection is the target; control points (usually 50 to 200) are taken on a regular grid in smooth areas (9x9 plane-fit residual below half a sampling unit)","not_applicable (pairwise rigid registration)","not_applicable","none","no joint optimization; in multi-view modelling each new view is registered against the merged data of all previously integrated views instead of only its neighbour, to avoid accumulated error","object-centred cylindrical or spherical coordinate map; views are reparameterized by interpolation and averaged in overlaps, with outlier handling","approximate initial transformation required: from the rotary-table set-up for side views, user-estimated rotation angles for top and bottom views, identity matrix in the two-view tests","6-DoF rigid transformation between range views; integrated object model as a spherical coordinate map, rendered views and wireframe","Symbolics 3620 Lisp Machine: 20 s for the Mozart pair (82 control points, 7 iterations) and 15 s for the tooth pair (88 control points, 6 iterations), whole process from control point selection to output",null,"not_verified",[49],{"relation":50,"title":51,"doi_or_url":52},"conference_version","Object modeling by registration of multiple range images (Proc. 1991 IEEE ICRA, pp. 2724-2729)","10.1109\u002FROBOT.1991.132043",{"id":5,"kind":54,"shortName":7,"title":8,"authors":55,"year":9,"venue":58,"venueType":59,"publisher":60,"volumeIssuePages":61,"doi":62,"arxivId":46,"url":63,"firstPublicDate":64,"publicationStatus":16,"metadataStatus":65,"fulltextStatus":15,"era":10,"classicReason":66,"codeUrl":46,"cluster":11,"topics":67,"mdpi":68,"verification":69,"label":6,"fulltextRoute":70,"versionRead":71,"addedByCensus":68},"method",[56,57],"Yang Chen","Gérard Medioni","Image and Vision Computing","journal","Elsevier","10(3):145-155","10.1016\u002F0262-8856(92)90066-c","https:\u002F\u002Fapi.crossref.org\u002Fworks\u002F10.1016\u002F0262-8856(92)90066-C","1991","metadata_verified","principle reused: the point-to-plane error metric is the default cost in libpointmatcher-based and many LiDAR odometry pipelines (e.g., tuna2024xicp Sec. II states point-to-plane remains preferred).",[11],false,"corrected","NTU institutional (Chrome)","Elsevier version of record, Image and Vision Computing 10(3):145-155 (April 1992); scanned PDF with OCR text layer; key numbers checked on rendered page images",[73,79,84],{"category":74,"model":75,"canonical":75,"role":76,"dataset":46,"specs":77,"locator":78},"other","range finder set-up described by Sato and Inokuchi (projector with programmable liquid crystal mask and CCD camera)","method input","space coding with projected stripe pattern and triangulation; accuracy in the neighbourhood of 1 mm; spatial resolution of range images 0.5 mm","p. 146; p. 151",{"category":80,"model":81,"canonical":81,"role":76,"dataset":46,"specs":82,"locator":83},"platform","rotary table","4 to 8 side views (8 views at 45 deg in the results) plus top and bottom views","pp. 152-153",{"category":85,"model":86,"canonical":86,"role":87,"dataset":46,"specs":18,"locator":88},"compute","Symbolics 3620 Lisp Machine","compute for runtime","p. 152",[],{"totalRows":91,"groupCount":92,"groups":93,"others":1175},143,12,[94,457,729,981],{"slug":95,"group":96,"sourceId":97,"sourceLabel":98,"table":99,"selfRows":100,"metrics":101,"seqs":115,"entrants":159,"cells":166,"outcomes":449,"locators":450,"hardware":453,"wordings":454,"notes":455},"pomerleau2013comparing-table-6","pomerleau2013comparing:Table 6","pomerleau2013comparing","Pomerleau et al., 2013","Table 6",72,[102,106,109,112],{"label":103,"unit":104,"statistic":105,"alignment":39},"translation error A50","m","median",{"label":107,"unit":104,"statistic":108,"alignment":39},"translation error A75","other: 75th percentile (A75)",{"label":110,"unit":104,"statistic":111,"alignment":39},"translation error A95","other: 95th percentile (A95)",{"label":113,"unit":114,"statistic":105,"alignment":39},"rotation error A50","rad",[116,120,122,124,127,129,131,134,136,138,141,143,145,148,150,152,155,157],{"dataset":117,"sequence":118,"environment":119},"Challenging Laser Registration (Pomerleau et al. 2012)","Apartment, EP (easy)","single floor with five rooms (indoor)",{"dataset":117,"sequence":121,"environment":119},"Apartment, MP (medium)",{"dataset":117,"sequence":123,"environment":119},"Apartment, HP (hard)",{"dataset":117,"sequence":125,"environment":126},"Stairs, EP (easy)","small staircase from indoor to outdoor",{"dataset":117,"sequence":128,"environment":126},"Stairs, MP (medium)",{"dataset":117,"sequence":130,"environment":126},"Stairs, HP (hard)",{"dataset":117,"sequence":132,"environment":133},"ETH, EP (easy)","large hallway with pillars and arches",{"dataset":117,"sequence":135,"environment":133},"ETH, MP (medium)",{"dataset":117,"sequence":137,"environment":133},"ETH, HP (hard)",{"dataset":117,"sequence":139,"environment":140},"Gazebo, EP (easy)","gazebo covered by vines in a public park (winter)",{"dataset":117,"sequence":142,"environment":140},"Gazebo, MP (medium)",{"dataset":117,"sequence":144,"environment":140},"Gazebo, HP (hard)",{"dataset":117,"sequence":146,"environment":147},"Wood, EP (easy)","dense vegetation around a small paved way (summer)",{"dataset":117,"sequence":149,"environment":147},"Wood, MP (medium)",{"dataset":117,"sequence":151,"environment":147},"Wood, HP (hard)",{"dataset":117,"sequence":153,"environment":154},"Plain, EP (easy)","small concave basin with alpine vegetation",{"dataset":117,"sequence":156,"environment":154},"Plain, MP (medium)",{"dataset":117,"sequence":158,"environment":154},"Plain, HP (hard)",[160,163],{"name":161,"methodId":5,"linkable":162,"proposed":68,"self":162},"point-to-plane ICP (libpointmatcher baseline, 70% trimmed)",true,{"name":164,"methodId":165,"linkable":162,"proposed":68,"self":68},"point-to-point ICP (libpointmatcher baseline, 75% trimmed)","besl1992icp",[167,171,174,177,180,182,184,186,188,190,192,194,196,198,200,202,203,205,207,209,211,213,215,217,218,220,222,224,225,227,228,230,232,235,237,239,241,243,245,247,249,252,254,256,258,260,262,264,266,269,271,273,275,276,278,280,282,285,287,289,290,292,294,296,298,301,303,305,307,309,311,313,315,318,320,321,322,324,325,327,329,331,333,335,336,338,340,342,344,347,349,351,353,355,357,359,360,362,364,365,366,368,369,371,372,375,377,379,381,383,385,387,389,391,393,395,397,398,400,402,403,406,407,409,410,412,414,416,417,420,422,424,426,428,430,432,433,436,438,440,442,444,446,448],[168,168,168,169,170,168,170,170,168],0,0.06,-1,[168,172,168,173,170,168,170,170,168],1,0.47,[168,175,168,176,170,168,170,170,168],2,2.11,[168,178,168,179,170,172,170,170,168],3,0.02,[172,168,168,181,170,168,170,170,168],0.13,[172,172,168,183,170,168,170,170,168],0.54,[172,175,168,185,170,168,170,170,168],1.54,[172,178,168,187,170,172,170,170,168],0.07,[168,168,172,189,170,168,170,170,168],0.2,[168,172,172,191,170,168,170,170,168],1.04,[168,175,172,193,170,168,170,170,168],2.98,[168,178,172,195,170,172,170,170,168],0.08,[172,168,172,197,170,168,170,170,168],0.46,[172,172,172,199,170,168,170,170,168],1.03,[172,175,172,201,170,168,170,170,168],2.32,[172,178,172,189,170,172,170,170,168],[168,168,175,204,170,168,170,170,168],1.35,[168,172,175,206,170,168,170,170,168],2.18,[168,175,175,208,170,168,170,170,168],3.66,[168,178,175,210,170,172,170,170,168],1.01,[172,168,175,212,170,168,170,170,168],1.29,[172,172,175,214,170,168,170,170,168],1.99,[172,175,175,216,170,168,170,170,168],3.24,[172,178,175,191,170,172,170,170,168],[168,168,178,219,170,168,170,170,168],0.09,[168,172,178,221,170,168,170,170,168],1.17,[168,175,178,223,170,168,170,170,168],3.49,[168,178,178,179,170,172,170,170,168],[172,168,178,226,170,168,170,170,168],0.35,[172,172,178,212,170,168,170,170,168],[172,175,178,229,170,168,170,170,168],2.57,[172,178,178,231,170,172,170,170,168],0.12,[168,168,233,234,170,168,170,170,168],4,0.61,[168,172,233,236,170,168,170,170,168],2.08,[168,175,233,238,170,168,170,170,168],4.64,[168,178,233,240,170,172,170,170,168],0.16,[172,168,233,242,170,168,170,170,168],0.94,[172,172,233,244,170,168,170,170,168],1.86,[172,175,233,246,170,168,170,170,168],3.38,[172,178,233,248,170,172,170,170,168],0.33,[168,168,250,251,170,168,170,170,168],5,2.05,[168,172,250,253,170,168,170,170,168],3.28,[168,175,250,255,170,168,170,170,168],5.5,[168,178,250,257,170,172,170,170,168],1.48,[172,168,250,259,170,168,170,170,168],1.81,[172,172,250,261,170,168,170,170,168],2.78,[172,175,250,263,170,168,170,170,168],4.75,[172,178,250,265,170,172,170,170,168],1.1,[168,168,267,268,170,168,170,170,168],6,0.1,[168,172,267,270,170,168,170,170,168],0.44,[168,175,267,272,170,168,170,170,168],6.06,[168,178,267,274,170,172,170,170,168],0.01,[172,168,267,173,170,168,170,170,168],[172,172,267,277,170,168,170,170,168],2.23,[172,175,267,279,170,168,170,170,168],6.86,[172,178,267,281,170,172,170,170,168],0.05,[168,168,283,284,170,168,170,170,168],7,0.6,[168,172,283,286,170,168,170,170,168],4.06,[168,175,283,288,170,168,170,170,168],16.3,[168,178,283,274,170,172,170,170,168],[172,168,283,291,170,168,170,170,168],1.92,[172,172,283,293,170,168,170,170,168],4.29,[172,175,283,295,170,168,170,170,168],11.2,[172,178,283,297,170,172,170,170,168],0.14,[168,168,299,300,170,168,170,170,168],8,4.18,[168,172,299,302,170,168,170,170,168],8.55,[168,175,299,304,170,168,170,170,168],19.6,[168,178,299,306,170,172,170,170,168],1.31,[172,168,299,308,170,168,170,170,168],3.84,[172,172,299,310,170,168,170,170,168],7.06,[172,175,299,312,170,168,170,170,168],14.8,[172,178,299,314,170,172,170,170,168],0.97,[168,168,316,317,170,168,170,170,168],9,0.11,[168,172,316,319,170,168,170,170,168],0.38,[168,175,316,236,170,168,170,170,168],[168,178,316,179,170,172,170,170,168],[172,168,316,323,170,168,170,170,168],0.28,[172,172,316,284,170,168,170,170,168],[172,175,316,326,170,168,170,170,168],1.71,[172,178,316,328,170,172,170,170,168],0.04,[168,168,330,323,170,168,170,170,168],10,[168,172,330,332,170,168,170,170,168],0.96,[168,175,330,334,170,168,170,170,168],3.51,[168,178,330,328,170,172,170,170,168],[172,168,330,337,170,168,170,170,168],0.49,[172,172,330,339,170,168,170,170,168],1.13,[172,175,330,341,170,168,170,170,168],3.18,[172,178,330,343,170,172,170,170,168],0.15,[168,168,345,346,170,168,170,170,168],11,1.87,[168,172,345,348,170,168,170,170,168],3.33,[168,175,345,350,170,168,170,170,168],6.95,[168,178,345,352,170,172,170,170,168],0.58,[172,168,345,354,170,168,170,170,168],1.58,[172,172,345,356,170,168,170,170,168],2.79,[172,175,345,358,170,168,170,170,168],4.57,[172,178,345,352,170,172,170,170,168],[168,168,92,361,170,168,170,170,168],0.25,[168,172,92,363,170,168,170,170,168],1.55,[168,175,92,263,170,168,170,170,168],[168,178,92,281,170,172,170,170,168],[172,168,92,367,170,168,170,170,168],0.39,[172,172,92,257,170,168,170,170,168],[172,175,92,370,170,168,170,170,168],4.21,[172,178,92,219,170,172,170,170,168],[168,168,373,374,170,168,170,170,168],13,1.25,[168,172,373,376,170,168,170,170,168],2.92,[168,175,373,378,170,168,170,170,168],6.62,[168,178,373,380,170,172,170,170,168],0.31,[172,168,373,382,170,168,170,170,168],1.19,[172,172,373,384,170,168,170,170,168],2.52,[172,175,373,386,170,168,170,170,168],5.15,[172,178,373,388,170,172,170,170,168],0.32,[168,168,390,356,170,168,170,170,168],14,[168,172,390,392,170,168,170,170,168],4.52,[168,175,390,394,170,168,170,170,168],7.86,[168,178,390,396,170,172,170,170,168],1.05,[172,168,390,201,170,168,170,170,168],[172,172,390,399,170,168,170,170,168],3.73,[172,175,390,401,170,168,170,170,168],6.82,[172,178,390,314,170,172,170,170,168],[168,168,404,405,170,168,170,170,168],15,0.42,[168,172,404,185,170,168,170,170,168],[168,175,404,408,170,168,170,170,168],4.15,[168,178,404,187,170,172,170,170,168],[172,168,404,411,170,168,170,170,168],0.51,[172,172,404,413,170,168,170,170,168],1.46,[172,175,404,415,170,168,170,170,168],3.09,[172,178,404,219,170,172,170,170,168],[168,168,418,419,170,168,170,170,168],16,1.3,[168,172,418,421,170,168,170,170,168],2.58,[168,175,418,423,170,168,170,170,168],5.58,[168,178,418,425,170,172,170,170,168],0.19,[172,168,418,427,170,168,170,170,168],1.21,[172,172,418,429,170,168,170,170,168],2.17,[172,175,418,431,170,168,170,170,168],3.76,[172,178,418,189,170,172,170,170,168],[168,168,434,435,170,168,170,170,168],17,2.35,[168,172,434,437,170,168,170,170,168],4.13,[168,175,434,439,170,168,170,170,168],8.85,[168,178,434,441,170,172,170,170,168],0.5,[172,168,434,443,170,168,170,170,168],2.02,[172,172,434,445,170,168,170,170,168],3.14,[172,175,434,447,170,168,170,170,168],6.33,[172,178,434,197,170,172,170,170,168],[],[451,452],"Table 6 (top)","Table 6 (bottom)",[],[],[456],"35 scan pairs per data set (overlap 0.30 to 0.99) with 64 Gaussian perturbations per level (EP easy, MP medium, HP hard); errors after registration against theodolite ground truth: translation = Euclidean norm (m), rotation = geodesic angle (rad); A50\u002FA75\u002FA95 quantiles",{"slug":458,"group":459,"sourceId":460,"sourceLabel":461,"table":462,"selfRows":418,"metrics":463,"seqs":471,"entrants":492,"cells":511,"outcomes":722,"locators":724,"hardware":725,"wordings":726,"notes":727},"lonet2019-table-1","lonet2019:Table 1","lonet2019","Li et al., 2019","Table 1",[464,468],{"label":465,"unit":466,"statistic":467,"alignment":40},"t_rel: average translational RMSE (%) on length of 100 m-800 m","%","mean",{"label":469,"unit":470,"statistic":467,"alignment":40},"r_rel: average rotational RMSE (deg\u002F100 m) on length of 100 m-800 m","deg\u002F100m",[472,476,478,480,482,484,486,490],{"dataset":473,"sequence":474,"environment":475},"KITTI odometry","07 (not used for training)","urban, country and highway driving, vehicle-mounted Velodyne HDL-64",{"dataset":473,"sequence":477,"environment":475},"08 (not used for training)",{"dataset":473,"sequence":479,"environment":475},"09 (not used for training)",{"dataset":473,"sequence":481,"environment":475},"10 (not used for training)",{"dataset":473,"sequence":483,"environment":475},"mean over 00-06 (training sequences)",{"dataset":473,"sequence":485,"environment":475},"mean over 07-10 (test sequences)",{"dataset":487,"sequence":488,"environment":489},"Ford Campus Vision and Lidar","Ford-1","urban campus driving with many moving vehicles, roof-mounted lidar",{"dataset":487,"sequence":491,"environment":489},"Ford-2",[493,495,497,500,502,505,507,509],{"name":494,"methodId":165,"linkable":162,"proposed":68,"self":68},"ICP-po2po (PCL)",{"name":496,"methodId":5,"linkable":162,"proposed":68,"self":162},"ICP-po2pl (PCL)",{"name":498,"methodId":499,"linkable":162,"proposed":68,"self":68},"GICP [30]","segal2009gicp",{"name":501,"methodId":46,"linkable":68,"proposed":68,"self":68},"CLS [34]",{"name":503,"methodId":504,"linkable":162,"proposed":68,"self":68},"LOAM [45] (authors' modified re-run)","loam2017_auro",{"name":506,"methodId":46,"linkable":68,"proposed":68,"self":68},"Velas et al. [35] (values from [35])",{"name":508,"methodId":460,"linkable":162,"proposed":162,"self":68},"LO-Net",{"name":510,"methodId":460,"linkable":162,"proposed":162,"self":68},"LO-Net+Mapping",[512,514,516,518,520,522,524,526,528,530,532,534,536,538,540,542,544,545,547,549,551,553,554,556,558,559,561,563,565,566,568,570,572,574,576,577,579,580,582,583,585,586,588,590,592,594,595,597,599,600,602,603,604,606,608,610,612,613,615,617,618,620,622,624,626,628,629,631,632,634,636,638,640,641,642,644,645,647,648,650,651,653,654,655,656,658,659,661,662,664,665,667,668,669,670,671,672,674,676,678,679,681,682,684,686,688,690,692,694,696,697,698,700,702,703,705,707,708,709,710,712,714,715,717,718,719,720,721],[168,168,168,513,170,168,170,170,168],5.17,[168,172,168,515,170,168,170,170,168],3.35,[168,168,172,517,170,168,170,170,168],10.04,[168,172,172,519,170,168,170,170,168],4.93,[168,168,175,521,170,168,170,170,168],6.93,[168,172,175,523,170,168,170,170,168],2.89,[168,168,178,525,170,168,170,170,168],8.91,[168,172,178,527,170,168,170,170,168],4.74,[168,168,233,529,170,168,170,170,168],7.13,[168,172,233,531,170,168,170,170,168],3.08,[168,168,250,533,170,168,170,170,168],7.76,[168,172,250,535,170,168,170,170,168],3.98,[168,168,267,537,170,168,170,170,168],8.2,[168,172,267,539,170,168,170,170,168],2.64,[168,168,283,541,170,168,170,170,168],16.23,[168,172,283,543,170,168,170,170,168],2.84,[172,168,168,363,170,168,170,170,168],[172,172,168,546,170,168,170,170,168],1.42,[172,168,172,548,170,168,170,170,168],4.42,[172,172,172,550,170,168,170,170,168],2.14,[172,168,175,552,170,168,170,170,168],3.95,[172,172,175,326,170,168,170,170,168],[172,168,178,555,170,168,170,170,168],6.13,[172,172,178,557,170,168,170,170,168],2.6,[172,168,233,386,170,168,170,170,168],[172,172,233,560,170,168,170,170,168],1.91,[172,168,250,562,170,168,170,170,168],4.01,[172,172,250,564,170,168,170,170,168],1.97,[172,168,267,515,170,168,170,170,168],[172,172,267,567,170,168,170,170,168],1.65,[172,168,283,569,170,168,170,170,168],5.68,[172,172,283,571,170,168,170,170,168],1.96,[175,168,168,573,170,168,170,170,168],0.64,[175,172,168,575,170,168,170,170,168],0.45,[175,168,172,354,170,168,170,170,168],[175,172,172,578,170,168,170,170,168],0.75,[175,168,175,564,170,168,170,170,168],[175,172,175,581,170,168,170,170,168],0.77,[175,168,178,306,170,168,170,170,168],[175,172,178,584,170,168,170,170,168],0.62,[175,168,233,277,170,168,170,170,168],[175,172,233,587,170,168,170,170,168],0.78,[175,168,250,589,170,168,170,170,168],1.38,[175,172,250,591,170,168,170,170,168],0.65,[175,168,267,593,170,168,170,170,168],3.07,[175,172,267,221,170,168,170,170,168],[175,168,283,596,170,168,170,170,168],5.11,[175,172,283,598,170,168,170,170,168],1.47,[178,168,168,191,170,168,170,170,168],[178,172,168,601,170,168,170,170,168],0.73,[178,168,172,550,170,168,170,170,168],[178,172,172,396,170,168,170,170,168],[178,168,175,605,170,168,170,170,168],1.95,[178,172,175,607,170,168,170,170,168],0.92,[178,168,178,609,170,168,170,170,168],3.46,[178,172,178,611,170,168,170,170,168],1.28,[178,168,233,176,170,168,170,170,168],[178,172,233,614,170,168,170,170,168],0.86,[178,168,250,616,170,168,170,170,168],2.15,[178,172,250,172,170,168,170,170,168],[178,168,267,619,170,168,170,170,168],10.54,[178,172,267,621,170,168,170,170,168],3.9,[178,168,283,623,170,168,170,170,168],14.78,[178,172,283,625,170,168,170,170,168],4.6,[233,168,168,627,170,168,170,170,168],0.69,[233,172,168,441,170,168,170,170,168],[233,168,172,630,170,168,170,170,168],1.18,[233,172,172,270,170,168,170,170,168],[233,168,175,633,170,168,170,170,168],1.2,[233,172,175,635,170,168,170,170,168],0.48,[233,168,178,637,170,168,170,170,168],1.51,[233,172,178,639,170,168,170,170,168],0.57,[233,168,233,204,170,168,170,170,168],[233,172,233,411,170,168,170,170,168],[233,168,250,643,170,168,170,170,168],1.15,[233,172,250,441,170,168,170,170,168],[233,168,267,646,170,168,170,170,168],1.68,[233,172,267,183,170,168,170,170,168],[233,168,283,649,170,168,170,170,168],1.78,[233,172,283,337,170,168,170,170,168],[250,168,168,652,170,168,170,170,168],1.77,[250,172,168,46,168,168,170,170,168],[250,168,172,523,170,168,170,170,168],[250,172,172,46,168,168,170,170,168],[250,168,175,657,170,168,170,170,168],4.94,[250,172,175,46,168,168,170,170,168],[250,168,178,660,170,168,170,170,168],3.27,[250,172,178,46,168,168,170,170,168],[250,168,233,663,170,168,170,170,168],3.12,[250,172,233,46,168,168,170,170,168],[250,168,250,666,170,168,170,170,168],3.22,[250,172,250,46,168,168,170,170,168],[250,168,267,46,168,168,170,170,168],[250,172,267,46,168,168,170,170,168],[250,168,283,46,168,168,170,170,168],[250,172,283,46,168,168,170,170,168],[267,168,168,673,170,168,170,170,168],1.7,[267,172,168,675,170,168,170,170,168],0.89,[267,168,172,677,170,168,170,170,168],2.12,[267,172,172,581,170,168,170,170,168],[267,168,175,680,170,168,170,170,168],1.37,[267,172,175,352,170,168,170,170,168],[267,168,178,683,170,168,170,170,168],1.8,[267,172,178,685,170,168,170,170,168],0.93,[267,168,233,687,170,168,170,170,168],1.09,[267,172,233,689,170,168,170,170,168],0.63,[267,168,250,691,170,168,170,170,168],1.75,[267,172,250,693,170,168,170,170,168],0.79,[267,168,267,695,170,168,170,170,168],2.27,[267,172,267,584,170,168,170,170,168],[267,168,283,206,170,168,170,170,168],[267,172,283,699,170,168,170,170,168],0.59,[283,168,168,701,170,168,170,170,168],0.56,[283,172,168,575,170,168,170,170,168],[283,168,172,704,170,168,170,170,168],1.08,[283,172,172,706,170,168,170,170,168],0.43,[283,168,175,581,170,168,170,170,168],[283,172,175,319,170,168,170,170,168],[283,168,178,607,170,168,170,170,168],[283,172,178,711,170,168,170,170,168],0.41,[283,168,233,713,170,168,170,170,168],0.81,[283,172,233,270,170,168,170,170,168],[283,168,250,716,170,168,170,170,168],0.83,[283,172,250,405,170,168,170,170,168],[283,168,267,265,170,168,170,170,168],[283,172,267,441,170,168,170,170,168],[283,168,283,212,170,168,170,170,168],[283,172,283,270,170,168,170,170,168],[723],"not_reported (NA)",[462],[],[],[728],"KITTI odometry metric: t_rel = average translational RMSE (%) and r_rel = average rotational RMSE (deg\u002F100 m) over 100-800 m lengths. LO-Net trained on KITTI 00-06 and tested on 07-10 and on Ford without fine-tuning; loop closure disabled for all methods. LOAM values outside brackets come from the authors' modified re-run; bracketed values are quoted from the LOAM paper [45]. Velas et al. values quoted from [35] (r_rel and Ford NA). ICP variants run with PCL. Truncated: per-sequence rows 00-06 (training sequences) omitted; the mean over them (mean-dagger) is kept.",{"slug":730,"group":731,"sourceId":732,"sourceLabel":733,"table":462,"selfRows":373,"metrics":734,"seqs":742,"entrants":768,"cells":790,"outcomes":975,"locators":976,"hardware":977,"wordings":978,"notes":979},"pwclonet2021-table-1","pwclonet2021:Table 1","pwclonet2021","Wang et al., 2021c",[735,738,740],{"label":736,"unit":466,"statistic":737,"alignment":39},"trel (average translational RMSE, %)","RMSE",{"label":739,"unit":466,"statistic":737,"alignment":39},"Mean on 07-10, trel",{"label":741,"unit":470,"statistic":737,"alignment":39},"Mean on 07-10, rrel (deg\u002F100m)",[743,746,748,750,752,754,756,758,760,762,764,766],{"dataset":473,"sequence":744,"environment":745},"00* (training)","vehicle, road",{"dataset":473,"sequence":747,"environment":745},"01* (training)",{"dataset":473,"sequence":749,"environment":745},"02* (training)",{"dataset":473,"sequence":751,"environment":745},"03* (training)",{"dataset":473,"sequence":753,"environment":745},"04* (training)",{"dataset":473,"sequence":755,"environment":745},"05* (training)",{"dataset":473,"sequence":757,"environment":745},"06* (training)",{"dataset":473,"sequence":759,"environment":745},"07 (test)",{"dataset":473,"sequence":761,"environment":745},"08 (test)",{"dataset":473,"sequence":763,"environment":745},"09 (test)",{"dataset":473,"sequence":765,"environment":745},"10 (test)",{"dataset":473,"sequence":767,"environment":745},"mean on 07-10 (test)",[769,771,773,775,777,779,781,783,785,788],{"name":770,"methodId":504,"linkable":162,"proposed":68,"self":68},"Full LOAM [31]",{"name":772,"methodId":165,"linkable":162,"proposed":68,"self":68},"ICP-po2po",{"name":774,"methodId":5,"linkable":162,"proposed":68,"self":162},"ICP-po2pl",{"name":776,"methodId":499,"linkable":162,"proposed":68,"self":68},"GICP [19]",{"name":778,"methodId":46,"linkable":68,"proposed":68,"self":68},"CLS [21]",{"name":780,"methodId":46,"linkable":68,"proposed":68,"self":68},"Velas et al. [22]",{"name":782,"methodId":460,"linkable":162,"proposed":68,"self":68},"LO-Net [10]",{"name":784,"methodId":46,"linkable":68,"proposed":68,"self":68},"DMLO [11]",{"name":786,"methodId":787,"linkable":162,"proposed":68,"self":68},"LOAM w\u002Fo mapping (published code run by authors)","loam2014",{"name":789,"methodId":732,"linkable":162,"proposed":162,"self":68},"Ours (PWCLO-Net)",[791,792,793,794,795,797,798,800,801,802,803,804,806,808,810,812,814,816,818,820,821,822,823,824,825,827,829,831,833,834,836,838,840,841,842,843,844,845,847,849,850,852,854,855,856,858,859,860,861,862,863,865,867,868,870,871,873,875,877,878,879,880,881,882,884,886,888,890,892,893,894,895,897,898,899,900,901,903,904,906,908,909,910,911,913,914,915,916,917,919,921,922,923,924,926,928,930,932,934,936,938,940,942,943,945,947,949,951,953,955,956,958,959,961,963,964,966,967,969,970,972,974],[168,168,168,265,170,168,170,170,168],[168,168,172,356,170,168,170,170,168],[168,168,175,185,170,168,170,170,168],[168,168,178,339,170,168,170,170,168],[168,168,233,796,170,168,170,170,168],1.45,[168,168,250,578,170,168,170,170,168],[168,168,267,799,170,168,170,170,168],0.72,[168,168,283,627,170,168,170,170,168],[168,168,299,630,170,168,170,170,168],[168,168,316,633,170,168,170,170,168],[168,168,330,637,170,168,170,170,168],[168,172,345,805,170,168,170,170,168],1.145,[168,175,345,807,170,168,170,170,168],0.498,[172,168,168,809,170,168,170,170,168],6.88,[172,168,172,811,170,168,170,170,168],11.21,[172,168,175,813,170,168,170,170,168],8.21,[172,168,178,815,170,168,170,170,168],11.07,[172,168,233,817,170,168,170,170,168],6.64,[172,168,250,819,170,168,170,170,168],3.97,[172,168,267,605,170,168,170,170,168],[172,168,283,513,170,168,170,170,168],[172,168,299,517,170,168,170,170,168],[172,168,316,521,170,168,170,170,168],[172,168,330,525,170,168,170,170,168],[172,172,345,826,170,168,170,170,168],7.763,[172,175,345,828,170,168,170,170,168],3.978,[175,168,168,830,170,168,170,170,168],3.8,[175,168,172,832,170,168,170,170,168],13.53,[175,168,175,316,170,168,170,170,168],[175,168,178,835,170,168,170,170,168],2.72,[175,168,233,837,170,168,170,170,168],2.96,[175,168,250,839,170,168,170,170,168],2.29,[175,168,267,652,170,168,170,170,168],[175,168,283,363,170,168,170,170,168],[175,168,299,548,170,168,170,170,168],[175,168,316,552,170,168,170,170,168],[175,168,330,555,170,168,170,170,168],[175,172,345,846,170,168,170,170,168],4.013,[175,175,345,848,170,168,170,170,168],1.968,[178,168,168,212,170,168,170,170,168],[178,168,172,851,170,168,170,170,168],4.39,[178,168,175,853,170,168,170,170,168],2.53,[178,168,178,646,170,168,170,170,168],[178,168,233,431,170,168,170,170,168],[178,168,250,857,170,168,170,170,168],1.02,[178,168,267,607,170,168,170,170,168],[178,168,283,573,170,168,170,170,168],[178,168,299,354,170,168,170,170,168],[178,168,316,564,170,168,170,170,168],[178,168,330,306,170,168,170,170,168],[178,172,345,864,170,168,170,170,168],1.375,[178,175,345,866,170,168,170,170,168],0.648,[233,168,168,176,170,168,170,170,168],[233,168,172,869,170,168,170,170,168],4.22,[233,168,175,839,170,168,170,170,168],[233,168,178,872,170,168,170,170,168],1.63,[233,168,233,874,170,168,170,170,168],1.59,[233,168,250,876,170,168,170,170,168],1.98,[233,168,267,607,170,168,170,170,168],[233,168,283,191,170,168,170,170,168],[233,168,299,550,170,168,170,170,168],[233,168,316,605,170,168,170,170,168],[233,168,330,609,170,168,170,170,168],[233,172,345,883,170,168,170,170,168],2.148,[233,175,345,885,170,168,170,170,168],0.995,[250,168,168,887,170,168,170,170,168],3.02,[250,168,172,889,170,168,170,170,168],4.44,[250,168,175,891,170,168,170,170,168],3.42,[250,168,178,657,170,168,170,170,168],[250,168,233,652,170,168,170,170,168],[250,168,250,435,170,168,170,170,168],[250,168,267,896,170,168,170,170,168],1.88,[250,168,283,652,170,168,170,170,168],[250,168,299,523,170,168,170,170,168],[250,168,316,657,170,168,170,170,168],[250,168,330,660,170,168,170,170,168],[250,172,345,902,170,168,170,170,168],3.218,[267,168,168,598,170,168,170,170,168],[267,168,172,905,170,168,170,170,168],1.36,[267,168,175,907,170,168,170,170,168],1.52,[267,168,178,199,170,168,170,170,168],[267,168,233,411,170,168,170,170,168],[267,168,250,191,170,168,170,170,168],[267,168,267,912,170,168,170,170,168],0.71,[267,168,283,673,170,168,170,170,168],[267,168,299,677,170,168,170,170,168],[267,168,316,680,170,168,170,170,168],[267,168,330,683,170,168,170,170,168],[267,172,345,918,170,168,170,170,168],1.748,[267,175,345,920,170,168,170,170,168],0.793,[283,168,283,601,170,168,170,170,168],[283,168,299,704,170,168,170,170,168],[283,168,316,265,170,168,170,170,168],[283,168,330,925,170,168,170,170,168],1.12,[283,172,345,927,170,168,170,170,168],1.008,[283,175,345,929,170,168,170,170,168],0.538,[299,168,168,931,170,168,170,170,168],15.99,[299,168,172,933,170,168,170,170,168],3.43,[299,168,175,935,170,168,170,170,168],9.4,[299,168,178,937,170,168,170,170,168],18.18,[299,168,233,939,170,168,170,170,168],9.59,[299,168,250,941,170,168,170,170,168],9.16,[299,168,267,525,170,168,170,170,168],[299,168,283,944,170,168,170,170,168],10.87,[299,168,299,946,170,168,170,170,168],12.72,[299,168,316,948,170,168,170,170,168],8.1,[299,168,330,950,170,168,170,170,168],12.67,[299,172,345,952,170,168,170,170,168],11.09,[299,175,345,954,170,168,170,170,168],6.405,[316,168,168,587,170,168,170,170,168],[316,168,172,957,170,168,170,170,168],0.67,[316,168,175,614,170,168,170,170,168],[316,168,178,960,170,168,170,170,168],0.76,[316,168,233,962,170,168,170,170,168],0.37,[316,168,250,575,170,168,170,170,168],[316,168,267,965,170,168,170,170,168],0.27,[316,168,283,284,170,168,170,170,168],[316,168,299,968,170,168,170,170,168],1.26,[316,168,316,693,170,168,170,170,168],[316,168,330,971,170,168,170,170,168],1.69,[316,172,345,973,170,168,170,170,168],1.085,[316,175,345,337,170,168,170,170,168],[],[462],[],[],[980],"KITTI odometry, trained on 00-06 (marked *) and tested on 07-10; trel = average translational RMSE (%) over 100-800 m subsequences; rows other than LOAM w\u002Fo mapping and Ours are copied from LO-Net [10]; LOAM is a full system with mapping, others are odometry only",{"slug":982,"group":983,"sourceId":984,"sourceLabel":985,"table":986,"selfRows":92,"metrics":987,"seqs":990,"entrants":1017,"cells":1034,"outcomes":1168,"locators":1169,"hardware":1170,"wordings":1171,"notes":1172},"rusinkiewicz2019symmetric-fig-5","rusinkiewicz2019symmetric:Fig. 5","rusinkiewicz2019symmetric","Rusinkiewicz, 2019","Fig. 5",[988],{"label":989,"unit":466,"statistic":467,"alignment":40},"percentage of successful ICP trials",[991,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015],{"dataset":992,"sequence":993,"environment":994},"bunny range scans (Turk and Levoy 1994)","20 iterations; rotation 20 deg, translation 10%","object-scale range scans",{"dataset":992,"sequence":996,"environment":994},"20 iterations; rotation 20 deg, translation 50%",{"dataset":992,"sequence":998,"environment":994},"20 iterations; rotation 60 deg, translation 10%",{"dataset":992,"sequence":1000,"environment":994},"20 iterations; rotation 60 deg, translation 50%",{"dataset":992,"sequence":1002,"environment":994},"100 iterations; rotation 20 deg, translation 10%",{"dataset":992,"sequence":1004,"environment":994},"100 iterations; rotation 20 deg, translation 50%",{"dataset":992,"sequence":1006,"environment":994},"100 iterations; rotation 60 deg, translation 10%",{"dataset":992,"sequence":1008,"environment":994},"100 iterations; rotation 60 deg, translation 50%",{"dataset":992,"sequence":1010,"environment":994},"500 iterations; rotation 20 deg, translation 10%",{"dataset":992,"sequence":1012,"environment":994},"500 iterations; rotation 20 deg, translation 50%",{"dataset":992,"sequence":1014,"environment":994},"500 iterations; rotation 60 deg, translation 10%",{"dataset":992,"sequence":1016,"environment":994},"500 iterations; rotation 60 deg, translation 50%",[1018,1020,1022,1024,1026,1028,1030,1032],{"name":1019,"methodId":165,"linkable":162,"proposed":68,"self":68},"Point-to-point",{"name":1021,"methodId":46,"linkable":68,"proposed":68,"self":68},"Quadratic (Mitra et al. 2004, on-demand)",{"name":1023,"methodId":5,"linkable":162,"proposed":68,"self":162},"Point-to-plane",{"name":1025,"methodId":46,"linkable":68,"proposed":68,"self":68},"Two-plane",{"name":1027,"methodId":984,"linkable":162,"proposed":162,"self":68},"Symmetric-RN",{"name":1029,"methodId":984,"linkable":162,"proposed":162,"self":68},"Symmetric",{"name":1031,"methodId":46,"linkable":68,"proposed":68,"self":68},"LM-Point-to-plane (Fitzgibbon 2001)",{"name":1033,"methodId":984,"linkable":162,"proposed":162,"self":68},"LM-Symmetric",[1035,1037,1039,1041,1042,1043,1044,1045,1046,1047,1049,1051,1053,1055,1056,1058,1060,1061,1063,1065,1067,1069,1071,1073,1075,1076,1078,1080,1082,1084,1085,1087,1089,1091,1092,1093,1095,1096,1097,1098,1099,1101,1102,1103,1105,1107,1108,1109,1110,1112,1114,1115,1117,1118,1119,1120,1121,1123,1125,1127,1128,1129,1130,1131,1132,1133,1134,1135,1136,1137,1138,1139,1140,1142,1143,1145,1146,1147,1148,1149,1150,1151,1152,1153,1154,1155,1157,1158,1159,1160,1161,1162,1163,1164,1166,1167],[168,168,168,1036,170,168,170,170,168],22,[172,168,168,1038,170,168,170,170,172],98,[175,168,168,1040,170,168,170,170,172],99,[178,168,168,1040,170,168,170,170,172],[233,168,168,1040,170,168,170,170,172],[250,168,168,1040,170,168,170,170,172],[267,168,168,1040,170,168,170,170,172],[283,168,168,1040,170,168,170,170,172],[168,168,172,283,170,168,170,170,172],[172,168,172,1048,170,168,170,170,172],69,[175,168,172,1050,170,168,170,170,172],66,[178,168,172,1052,170,168,170,170,172],73,[233,168,172,1054,170,168,170,170,172],81,[250,168,172,1054,170,168,170,170,172],[267,168,172,1057,170,168,170,170,172],78,[283,168,172,1059,170,168,170,170,172],89,[168,168,175,175,170,168,170,170,172],[172,168,175,1062,170,168,170,170,172],53,[175,168,175,1064,170,168,170,170,172],62,[178,168,175,1066,170,168,170,170,172],65,[233,168,175,1068,170,168,170,170,172],77,[250,168,175,1070,170,168,170,170,172],82,[267,168,175,1072,170,168,170,170,172],58,[283,168,175,1074,170,168,170,170,172],79,[168,168,178,175,170,168,170,170,172],[172,168,178,1077,170,168,170,170,172],40,[175,168,178,1079,170,168,170,170,172],44,[178,168,178,1081,170,168,170,170,172],51,[233,168,178,1083,170,168,170,170,172],59,[250,168,178,1066,170,168,170,170,172],[267,168,178,1086,170,168,170,170,172],47,[283,168,178,1088,170,168,170,170,172],70,[168,168,233,1090,170,168,170,170,172],92,[172,168,233,1040,170,168,170,170,172],[175,168,233,1040,170,168,170,170,172],[178,168,233,1094,170,168,170,170,172],100,[233,168,233,1040,170,168,170,170,172],[250,168,233,1040,170,168,170,170,172],[267,168,233,1040,170,168,170,170,172],[283,168,233,1040,170,168,170,170,172],[168,168,250,1100,170,168,170,170,172],67,[172,168,250,1059,170,168,170,170,172],[175,168,250,1070,170,168,170,170,172],[178,168,250,1104,170,168,170,170,172],91,[233,168,250,1106,170,168,170,170,172],85,[250,168,250,1106,170,168,170,170,172],[267,168,250,1059,170,168,170,170,172],[283,168,250,1104,170,168,170,170,172],[168,168,267,1111,170,168,170,170,172],49,[172,168,267,1113,170,168,170,170,172],80,[175,168,267,1054,170,168,170,170,172],[178,168,267,1116,170,168,170,170,172],86,[233,168,267,1070,170,168,170,170,172],[250,168,267,1116,170,168,170,170,172],[267,168,267,1113,170,168,170,170,172],[283,168,267,1106,170,168,170,170,172],[168,168,283,1122,170,168,170,170,172],43,[172,168,283,1124,170,168,170,170,172],71,[175,168,283,1126,170,168,170,170,172],68,[178,168,283,1057,170,168,170,170,172],[233,168,283,1126,170,168,170,170,172],[250,168,283,1052,170,168,170,170,172],[267,168,283,1052,170,168,170,170,172],[283,168,283,1057,170,168,170,170,172],[168,168,299,1040,170,168,170,170,172],[172,168,299,1040,170,168,170,170,172],[175,168,299,1040,170,168,170,170,172],[178,168,299,1094,170,168,170,170,172],[233,168,299,1040,170,168,170,170,172],[250,168,299,1040,170,168,170,170,172],[267,168,299,1040,170,168,170,170,172],[283,168,299,1040,170,168,170,170,172],[168,168,316,1141,170,168,170,170,172],88,[172,168,316,1059,170,168,170,170,172],[175,168,316,1144,170,168,170,170,172],83,[178,168,316,1104,170,168,170,170,172],[233,168,316,1106,170,168,170,170,172],[250,168,316,1106,170,168,170,170,172],[267,168,316,1059,170,168,170,170,172],[283,168,316,1104,170,168,170,170,172],[168,168,330,1068,170,168,170,170,172],[172,168,330,1070,170,168,170,170,172],[175,168,330,1070,170,168,170,170,172],[178,168,330,1141,170,168,170,170,172],[233,168,330,1144,170,168,170,170,172],[250,168,330,1156,170,168,170,170,172],87,[267,168,330,1054,170,168,170,170,172],[283,168,330,1116,170,168,170,170,172],[168,168,345,1124,170,168,170,170,172],[172,168,345,1052,170,168,170,170,172],[175,168,345,1048,170,168,170,170,172],[178,168,345,1113,170,168,170,170,172],[233,168,345,1048,170,168,170,170,172],[250,168,345,1165,170,168,170,170,172],74,[267,168,345,1165,170,168,170,170,172],[283,168,345,1074,170,168,170,170,172],[],[986],[],[],[1173,1174],"Numerals printed in Fig. 5 heatmap cells: % of 1000 random initial transforms (given rotation about a random axis, translation as fraction of mesh size), averaged over all bunny scan pairs with IOU > 20%, that end within 1% of mesh size of ground truth; 4 of 24 cells per variant and iteration budget transcribed","Same setting as other Fig. 5 rows",[1176,1183,1190,1197,1202,1207,1214,1220],{"group":1177,"slug":1178,"sourceLabel":6,"table":1179,"selfRows":283,"datasets":1180},"chen1992pointtoplane:Fig. 5d and Fig. 6e histogram labels","chen1992pointtoplane-fig-5d-and-fig-6e-histogram-labels","Fig. 5d and Fig. 6e histogram labels",[1181,1182],"authors' range images (Mozart bust)","authors' range images (model tooth)",{"group":1184,"slug":1185,"sourceLabel":1186,"table":1187,"selfRows":267,"datasets":1188},"zhang2024globalbimreg:Table 2","zhang2024globalbimreg-table-2","Zhang et al., 2024b","Table 2",[1189],"ISPRS benchmark on indoor modelling",{"group":1191,"slug":1192,"sourceLabel":1193,"table":1194,"selfRows":267,"datasets":1195},"zhou2016fgr:Table 3","zhou2016fgr-table-3","Zhou et al., 2016","Table 3",[1196],"Synthetic range images",{"group":1198,"slug":1199,"sourceLabel":6,"table":1200,"selfRows":233,"datasets":1201},"chen1992pointtoplane:Text p. 152","chen1992pointtoplane-text-p-152","Text p. 152",[1181,1182],{"group":1203,"slug":1204,"sourceLabel":98,"table":1205,"selfRows":178,"datasets":1206},"pomerleau2013comparing:Text Sec. 5.2.4","pomerleau2013comparing-text-sec-5-2-4","Text Sec. 5.2.4",[117],{"group":1208,"slug":1209,"sourceLabel":1210,"table":1211,"selfRows":175,"datasets":1212},"magnusson2015beyondpoints:Fig. 3 (execution-time table)","magnusson2015beyondpoints-fig-3-execution-time-table","Magnusson et al., 2015","Fig. 3 (execution-time table)",[1213],"ETH Challenging Laser Registration (six data sets)",{"group":1215,"slug":1216,"sourceLabel":1217,"table":1218,"selfRows":172,"datasets":1219},"zhang2024_3dlidarslam_survey:Table 8","zhang2024-3dlidarslam-survey-table-8","Zhang et al., 2024a","Table 8",[473],{"group":1221,"slug":1222,"sourceLabel":1217,"table":1223,"selfRows":172,"datasets":1224},"zhang2024_3dlidarslam_survey:Table 9","zhang2024-3dlidarslam-survey-table-9","Table 9",[473],1790510664540]