Real-time detection of out-of-plane objects in stereo vision

Authors:
Weiguang Guan;Patricia Monger
Affiliations:
Dept. of Research and High Performance Computing, McMaster University, Hamilton, Ontario, Canada;Dept. of Research and High Performance Computing, McMaster University, Hamilton, Ontario, Canada
Venue:
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Year:
2006

Citing 3
Cited 1

Multiple view geometry in computer visiond

Multiple view geometry in computer visiond
A Specialized Multibaseline Stereo Technique for Obstacle Detection

CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Fixed Point Probability Field for Complex Occlusion Handling

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01

Combining Line and Point Correspondences for Homography Estimation

ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes an automatic approach to detecting objects appearing in front of planar background. A planar homography is estimated with high accuracy in an off-line initialization phase. Given a pair of binocular images, we apply the estimated homography to one of the images, and then compute a similarity map between the transformed image and the other. Normalized cross-correlation is used in the computation of the similarity map to measure the similarity between neighborhoods of overlapping pixels. Normalized cross-correlation measure is superior to absolute difference in alleviating the influence of image noise and small mis-alignment caused by imperfect homography estimation. The similarity map with pixel intensities ranging between 0 and 1 leads to an easy detection of out-of-plane objects because the values of pixels corresponding to planar background are close to 1. Tracking could be incorporated with our out-of-plane object detection method to further improve robustness in live video applications. This approach has been used in tracking people and demonstrated reliable performance.