Jun Wang   

Professor
Supervisor of Doctorate Candidates

MORE> Recommended Ph.D.Supervisor Recommended MA Supervisor
Language:English

Paper Publications

Title of Paper:Object Detection and Tracking under Occlusion for Object-Level RGB-D Video Segmentation

Hits:

Affiliation of Author(s):机电学院

Journal:IEEE Trans Multimedia

Abstract:RGB-D video segmentation is important for many applications, including scene understanding, object tracking, and robotic grasping. However, to segment RGB-D frames over a long video sequence into globally consistent segmentation is still a challenging problem. Current methods often lose pixel correspondences between frames under occlusion and, thus, fail to generate consistent and continuous segmentation results. To address this problem, we propose a novel spatiotemporal RGB-D video segmentation framework that automatically segments and tracks objects with continuity and consistency over time. Our approach first produces consistent segments in some keyframes by region clustering, and then propagates the segmentation result to a whole video sequence via a mask propagation scheme in bilateral space. Instead of exploiting local optical, flow information to establish correspondences between adjacent frames, we leverage scale-invariant feature transform (SIFT) flow and bilateral representation to solve inconsistency under occlusion. Moreover, our method automatically extracts multiple objects of interest and tracks them without any user input hint. A variety of experiments demonstrates effectiveness and robustness of our proposed method. © 1999-2012 IEEE.

ISSN No.:1520-9210

Translation or Not:no

Date of Publication:2018-03-01

Co-author:谢乾,Remil, Oussama,Guo, Yanwen,Wang, Meng,Jun Wang

Correspondence Author:Jun Wang,Mingqiang Wei

Copyright©2018- Nanjing University of Aeronautics and Astronautics·Informationization Department(Informationization Technology Center)
Click:    MOBILE Version

Open time:..

The Last Update Time: ..