The New College Vision and Laser Data Set

By Mike Smith, Ian A. Baldwin, Winston Churchill, Rohan Paul, Paul M. Newman. Int. J. Robotics Res., 2009

343 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/80ccc2feda0a65344bf282af782527b68d086857

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving (2017, positive): “In a similar fashion, the New College data set [96] is a 2.2 km trajectory in outdoor environment with cameras and lasers.”
Evaluating Egomotion and Structure-from-Motion Approaches Using the TUM RGB-D Benchmark (2012, methodology): “For laser-and camera-based SLAM systems, there are several well-known datasets such as the Freiburg, Intel, Rawseeds and Newcollege datasets [35]–[37].”
OctoMap : A Probabilistic , Flexible , and Compact 3 D Map Representation for Robotic Systems (2010, methodology): “In addition, we use laser range data of the New College data set [18].”
Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation (2013, positive): “We conducted tests with the following community data sets: NewCollege (NC) and CityCentre (CiC) [16]; Lip6Indoor (L6I) and Lip6Outdoor (L6O) [29]; 70 km [30]; New-CollegeOmni (NCO) [43]; CrowdedCanteen (CrC) [44]; BicoccaIndoor-2009-02-25b (BI), BovisaOutdoor-2008-10-04 (BO) and BovisaMixed-2008-10-”
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016, neutral): “nocular stereo images). Topic References Data IMU GPS Labels LIDAR2D LIDAR3D LOC MAP RGB RGBD Stereo Front-ends and back-ends in small / medium scale scenarios [293] X X X [319] X X X [233] X X X X X [283] X X X X [141, 239] X [134, 317, 318] X X X [122] X X X X X X X X [39] X X X X X [254] X X X X ”
A benchmark for the evaluation of RGB-D SLAM systems (2012, methodology): “To this aim, the OpenNI-driver has an option to register the depth image to the color image using a Z-buffer automatically.”
Are we ready for autonomous driving? The KITTI vision benchmark suite (2012, neutral): “3 Mpx X X New College [42] outdoor 1 2.”
G2o: A general framework for graph optimization (2011, methodology): “The BA real world datasets and the scale-drift dataset used for evaluating g(2)o: the left image shows the Venice dataset, whereas the middle image depicts the New College dataset [24].”
Complex urban dataset with multi-level sensors from highly diverse urban environments (2019, methodology): “The New College Dataset (Smith et al. 2009) provides data from a campus and a park that were obtained using a Segway robotic platform.”
PL-SLAM: A Stereo SLAM System Through the Combination of Points and Line Segments (2017, methodology): “employed in [46] for four different datasets: Oxford dataset [47], sequence 4 in Malaga dataset [48], sequence 7 in KITTI dataset [49], and i3tf dataset [34].”