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Title: Benchmarking Pedestrian Odometry: The Brown Pedestrian Odometry Dataset (BPOD)
This paper presents the Brown Pedestrian Odometry Dataset (BPOD) for benchmarking visual odometry algo- rithms on data from head-mounted sensors. This dataset was captured with stereo and RGB streams from RealSense cameras with rolling and global shutters in 12 diverse in- door and outdoor locations on Brown University’s cam- pus. Its associated ground-truth trajectories were gener- ated from third-person videos that documented the recorded pedestrians’ positions relative to stick-on markers placed along their paths. We evaluate the performance of canoni- cal approaches representative of direct, feature-based, and learning-based visual odometry methods on BPOD. Our finding is that current methods which are successful on other benchmarks fail on BPOD. The failure modes cor- respond in part to rapid pedestrian rotation, erratic body movements, etc. We hope this dataset will play a significant role in the identification of these failure modes and in the design, development, and evaluation of pedestrian odome- try algorithms.  more » « less
Award ID(s):
1910530
NSF-PAR ID:
10387071
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
3DV
ISSN:
0219-6921
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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