Evaluation of moving object segmentation comparing 6D-vision and monocular motion constraints

2008 23rd International Conference Image and Vision Computing New Zealand, IVCNZ

Volumn , Issue , 2008, Pages

  Vaudrey, Tobi ^a   Wedel, Andreas ^b   Rabe, Clemens ^b   Klappstein, Jens ^b   Klette, Reinhard ^a  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b DAIMLER AG   (Germany)

Author keywords

Driver assistance systems (DAS); Evaluations; Motion detection; Segmentation; Stereo analysis

Indexed keywords

AUTOMOBILE ELECTRONIC EQUIPMENT; DETECTOR CIRCUITS; IMAGE SEGMENTATION; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MILITARY ELECTRONIC COUNTERMEASURES; PIPELINES; TRACKING (POSITION);

DRIVER ASSISTANCE SYSTEMS (DAS); EVALUATIONS; MOTION DETECTION; SEGMENTATION; STEREO ANALYSIS;

AUTOMOBILE DRIVERS;

EID: 63049086712     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IVCNZ.2008.4762126     Document Type: Conference Paper

References (12)

1. X. Armangué, H. Araújo, and J. Salvi. Differential epipolar constraint in mobile robot egomotion estimation. In Proc. IEEE Int. Conf. Pattern Recognition, pages 599-602, 2002.
2. Y. Boykov and V. Kolmogorov. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. In Energy Minimization Methods in Computer Vision and Pattern Recognition, pages 359-374, 2001.
3. U. Franke, C. Rabe, H. Badino, and S. Gehrig. 6d-vision: Fusion of stereo and motion for robust environment perception. In Proc. DAGM Symposium, pages 216-223, 2005.
4. R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge Press, second edition, 2003.
5. H. Hirschmüller. Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information. In Proc. IEEE Conf. Computer Vision Pattern Recognition, volume 2, pages 807-814, 2005.
6. J. Klappstein, F. Stein, and U. Franke. Monocular motion detection using spatial constraints in a unified manner. In Proc. IEEE Intelligent Vehicles Symposium, 2006.
7. J. Klappstein, F. Stein, and U. Franke. Applying kalman filtering to road homography estimation. In Proc. Workshop Planning Perception Navigation Intelligent Vehicles (in conjunction with IEEE Int. Conf. Robotics Automation), 2007.
8. J. Klappstein, F. Stein, and U. Franke. Detectability of moving objects using correspondences over two and three frames. In Pattern Recognition (Proc. DAGM), pages 112-121. Springer, 2007.
9. C. Rabe, U. Franke, and S. Gehrig. Fast detection of moving objects in complex scenarios. In Proc. Proc. IEEE Intelligent Vehicles Symposium, pages 398-403, 2007.
10. C. Tomasi and T. Kanade. Detection and tracking of point features. Technical report CMU-CS-91-132, Carnegie Mellon University, 1991.
11. T. Vaudrey, D. Gruber, A. Wedel, and J. Klappstein. Space-time multi-resolution banded graph-cut for fast segmentation. In Proc. DAGM Symposium, pages 203-213. Springer, 2008.
12. G. Welch and G. Bishop. An introduction to the Kalman filter. Technical Report TR 95-041, University of North Carolina at Chapel Hill, Department of Computer Science, 1995.