Towards Generic 3D Tracking in RGBD Videos: Benchmark and Baseline

Jinyu Yang1,2; Zhongqun Zhang2; Zhe Li1; Hyung Jin Chang2; Ales Leonardis2; Feng Zheng1

10.1007/978-3-031-20047-2_7

2022

17th European Conference on Computer Vision (ECCV)

0302-9743

1611-3349

978-3-031-20046-5

LECT NOTES ARTIF INT

13682

OCT 23-27, 2022

null,Tel Aviv,ISRAEL

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

SPRINGER INTERNATIONAL PUBLISHING AG

Tracking in 3D scenes is gaining momentum because of its numerous applications in robotics, autonomous driving, and scene understanding. Currently, 3D tracking is limited to specific model-based approaches involving point clouds, which impedes 3D trackers from applying in natural 3D scenes. RGBD sensors provide a more reasonable and acceptable solution for 3D object tracking due to their readily available synchronised color and depth information. Thus, in this paper, we investigate a novel problem: is it possible to track a generic (class-agnostic) 3D object in RGBD videos and predict 3D bounding boxes of the object of interest? To inspire research on this topic, we newly construct a standard benchmark for generic 3D object tracking, `Track-it-in-3D', which contains 300 RGBD video sequences with dense 3D annotations and corresponding evaluation protocols. Furthermore, we propose an effective tracking baseline to estimate 3D bounding boxes for arbitrary objects in RGBD videos, by fusing appearance and spatial information effectively. Resources are available on https://github.com/yjybuaa/Track- it-in-3D.

Object tracking 3D object tracking RGBD data

第一 ; 通讯

英语

CPCI-S

Computer Science ; Imaging Science & Photographic Technology

Computer Science, Artificial Intelligence ; Imaging Science & Photographic Technology

WOS:000904116000007

Web of Science

1.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
2.University of Birmingham, Birmingham, United Kingdom

Jinyu Yang,Zhongqun Zhang,Zhe Li,et al. Towards Generic 3D Tracking in RGBD Videos: Benchmark and Baseline[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2022.