Abstract
Motion discontinuities arise when there are occlusions or multiple moving objects in the scene that is imaged. Conventional regularization techniques use smoothness constraints but are not applicable to motion discontinuities. In this paper, we show that discontinuous (or multiple) motion estimation can be viewed as a multicomponent harmonic retrieval problem. From this viewpoint, a number of established techniques for harmonic retrieval can be applied to solve the challenging problem of discontinuous (or multiple) motion. Compared with existing techniques, the resulting algorithm is not iterative, which not only implies computational efficiency but also obviates concerns regarding convergence or local minima. It also adds flexibility to spatio-temporal techniques which have suffered from lack of explicit modeling of discontinuous motion. Experimental verification of our framework on both synthetic data as well as real image data is provided.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1242-1257 |
| Number of pages | 16 |
| Journal | IEEE Transactions on Image Processing |
| Volume | 7 |
| Issue number | 9 |
| DOIs | |
| State | Published - 1998 |
Bibliographical note
Funding Information:Manuscript received January 20, 1995; revised February 20, 1997. The work of W.-G. Chen and N. Nandhakumar was supported by the National Science Foundation under Grant IRI-91109584. The work of G. B. Giannakis was supported by the National Science Foundation under Grant MIP9210230 and by the Office of Naval Research under Grant N00014-93-1-0485. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Eric Dubois.
Keywords
- Compression
- Computer vision
- Discontinuous motion
- Harmonic retrieval
- Motion estimation
- Multimedia
- Multiple motion
- Video communication