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Technical Program
Paper Detail
| Paper: | WP-P1.7 |
| Session: | Visual Object/Event Detection, Segmentation, and Classification |
| Time: | Wednesday, October 11, 14:20 - 17:00 |
| Presentation: |
Poster
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| Title: |
ROBUST GROUND PLANE DETECTION WITH NORMALIZED HOMOGRAPHY IN MONOCULAR SEQUENCES FROM A ROBOT PLATFORM |
| Authors: |
Jin Zhou; Arizona State University | | | | | Baoxin Li; Arizona State University | | |
| Abstract: |
We present a homography-based approach to detect the ground plane from monocular sequences captured by a robot platform. By assuming that the camera is fixed on the robot platform and can at most rotate horizontally, we derive the constraints that the homograph of the ground plane must satisfy and then use these constraints to design algorithms for detecting the ground plane. The resultant algorithm is not only more efficient and robust, but also able to avoid false detection due to virtual planes in homography fitting. We present experiments with real data from a robot platform to validate the proposed approaches. |
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