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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Aach, T. Dumbgen, L. Mester, R. Toth, D. |
| Copyright Year | 2001 |
| Description | Author affiliation: Inst. for Signal Process., Univ. of Lubeck, Germany (Aach, T.) |
| Abstract | We describe an algorithm for change detection which is insensitive to both slow and fast temporal variations of scene illumination. Our algorithm is based on statistical decision theory by using a Bayesian approach. The goal is to detect only temporal changes which are induced by true scene changes, like motion, but not changes due to varying illumination or noise. To this end, our algorithm uses a simple illumination model which is invariant to common camera nonlinearities like gamma-nonlinearity. This is combined with a model for the influence of noise as well as an a priori model for the expected properties of the sought change masks. Key ingredients of the resulting algorithm are a suitable test statistic and an adaptive threshold mechanism. As the algorithm can be applied in a noniterative manner, it is also computationally attractive. |
| Sponsorship | IEEE Signal Process. Soc |
| Starting Page | 640 |
| Ending Page | 643 |
| File Size | 398786 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780367251 |
| DOI | 10.1109/ICIP.2001.958200 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-10-07 |
| Publisher Place | Greece |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bayesian methods Motion detection Lighting Layout Signal processing algorithms Change detection algorithms Object oriented modeling Testing Decision theory Cameras |
| Content Type | Text |
| Resource Type | Article |
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