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Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical FlowDynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.
Document ID
20080018465
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Talukder, Ashit
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Matthies, Larry
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 24, 2013
Publication Date
September 28, 2004
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Meeting Information
Meeting: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2004
Location: Sendai
Country: Japan
Start Date: September 28, 2004
End Date: October 2, 2004
Sponsors: Institute of Electrical and Electronics Engineers
Distribution Limits
Public
Copyright
Other
Keywords
moving object detection
egomotion
dynamic scene analysis
visual odometry

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