ESTIMATION OF MULTI RESOLUSIONAL OPTICAL FLOW BASED ON DYNAMIC BAYESIAN NETWORK(INTERNATIONAL Workshop on Advanced Image Technology 2008)
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概要
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A number of methods have been proposed for determining object shape from image sequences. This strategy is called Structure from Motion (SFM). SFM is one of the central subjects in the computer vision. Although, the methods based on factorization are the current mainstream, these methods require feature point matching through multi-frames in advance, which is a difficult problem itself. Moreover, the dense object shape cannot be reconstructed by these methods. In this study, we examine a method for estimating dense optical flow based on gradient equation from the viewpoint of considering a dense object shape reconstruction. Because detection of optical flow is essentially ill-posed problems, which is the aperture problem, other constraints on optical flow have to be considered. Additionally, in the case of that the motion between consecutive frames is larger than the period of the principal intensity pattern, estimation of the correct optical flow is crucially difficult because of alias. For overcoming these two problems, we propose a multi-scale method using a Bayesian strategy. In our method, original images are decomposed into multi-scale image components which have a different spatial frequency band respectively. Information of variables is sequentially propagated from a low-frequency image component to a high-frequency image component. The model which is used to realize the above scheme can be defined using the dynamic Bayesian network. Additionally, the inference procedure on this model can be constructed using the belief propagation (BP) and the expectation-maximization (EM) algorithm. The effectiveness of this proposed algorithm is confirmed through simulations.
- 社団法人電子情報通信学会の論文
- 2007-12-31
著者
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Tagawa Norio
Graduate School of Engineering, Tokyo Metropolitan University
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Tagawa Norio
Graduate School Of Electrical Engineering Tokyo Metropolitan University
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Naganuma Shoichi
Graduate School of Engineering, Tokyo Metropolitan University
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Naganuma Shoichi
Graduate School Of Electrical Engineering Tokyo Metropolitan University
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