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Recursive Optical Flow Estimation - Adaptive Filtering Approach (1995)
| Content Provider | CiteSeerX |
|---|---|
| Author | Elad, M. Feuer, A. |
| Abstract | This paper presents a new approach towards the problem of recursive optical flow estimation from image sequences based on the differential framework proposed by Horn & Schunck. We show that gain is achieved both from computational and accuracy points of view when treating the estimation task recursively. Incorporation of the temporal axis into the estimation process is done by combining a temporal smoothness assumption on the optical flow. RLS and LMS recursive optical flow estimation algorithms are derived and tested. 1. Introduction Optical flow is the displacement field related to each of the pixels in an image sequence. Such displacement field results from the apparent motion of the image brightness in time. Estimating the optical flow is a fundamental problem in low level vision, and can undoubtedly serve many applications in image sequence processing. There are many different methods to estimate the optical flow. This paper focuses on a generalization of the method proposed by ... |
| File Format | |
| Volume Number | 9 |
| Journal | Journal of Visual Communication and Image Representation |
| Language | English |
| Publisher Date | 1995-01-01 |
| Access Restriction | Open |
| Subject Keyword | Optical Flow Image Sequence Temporal Axis Displacement Field Result Horn Schunck Accuracy Point Estimation Task Low Level Vision Many Different Method Many Application Image Sequence Processing Temporal Smoothness Assumption Estimation Process Introduction Optical Flow New Approach Displacement Field Image Brightness Fundamental Problem Apparent Motion Differential Framework Recursive Optical Flow Estimation |
| Content Type | Text |
| Resource Type | Article |
