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Description: The problem of image registration subsumes a number of problems and techniques in multiframe
image analysis, including the computation of optic flow (general pixel-based motion), stereo
correspondence, structure from motion, and feature tracking. We present a new registration
algorithm based on spline representations of the displacement field which can be specialized to
solve all of the above mentioned problems. In particular, we show how to compute local flow,
global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of
the above problems. Using a spline-based description of the flow removes the need for overlapping
correlation windows, and produces an explicit measure of the correlation between adjacent flow
estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D
projective scene geometry. We also provide results on a number of standard motion sequences.
Platform: |
Size: 486459 |
Author: 刘长乐 |
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Description: The problem of image registration subsumes a number of problems and techniques in multiframe
image analysis, including the computation of optic flow (general pixel-based motion), stereo
correspondence, structure from motion, and feature tracking. We present a new registration
algorithm based on spline representations of the displacement field which can be specialized to
solve all of the above mentioned problems. In particular, we show how to compute local flow,
global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of
the above problems. Using a spline-based description of the flow removes the need for overlapping
correlation windows, and produces an explicit measure of the correlation between adjacent flow
estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D
projective scene geometry. We also provide results on a number of standard motion sequences.
Platform: |
Size: 486400 |
Author: 刘长乐 |
Hits:
Description: 基于概率框架的立体视觉匹配和运动估计方法-A Probabilistic Framework for Correspondence and Egomotion Estimation
Platform: |
Size: 261120 |
Author: wangke |
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Description: Most of my current work focuses on tracking pedestrians mobile platforms. The idea is to equip robots or cars with vision systems that can oversee the traffic situation around the car and that can give an early warning for dangerous situations. The system finds people, tracks them, and determines their trajectory relative to the mobile platform which the images are taken. We tested our system in busy urban scenarios, and provide the corresponding dataset for other researchers. The underlying methodology is to integrate different functionalities that thus far have been mainly developed separately in computer vision: recognition - tracking - 3D reconstruction for egomotion extraction.
-Most of my current work focuses on tracking pedestrians mobile platforms. The idea is to equip robots or cars with vision systems that can oversee the traffic situation around the car and that can give an early warning for dangerous situations. The system finds people, tracks them, and determines their trajectory relative to the mobile platform which the images are taken. We tested our system in busy urban scenarios, and provide the corresponding dataset for other researchers. The underlying methodology is to integrate different functionalities that thus far have been mainly developed separately in computer vision: recognition - tracking - 3D reconstruction for egomotion extraction.
Platform: |
Size: 5445632 |
Author: Taher |
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