For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Adaptive Decomposition of Dynamic Scene into Object-Based Distribution Components Based on Mixture Model Framework
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2005/04/01
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
mixture model, EM algorithm, BIC criterion, segmentation, object recognition, computer vision,
Full Text: PDF>>
This paper newly proposes a method to automatically decompose real scene images into multiple object-oriented component regions. First, histogram patterns of a specific image feature, such as intensity or hue value, are estimated from image sequence and stored up. Next, Gaussian distribution parameters which correspond to object components involved in the scene are estimated by applying the EM algorithm to the accumulated histogram. The number of the components is simultaneously estimated by evaluating the minimum value of Bayesian Information Criterion (BIC). This method can be applied to a variety of computer vision issues, for example, the color image segmentation and the recognition of scene situation transition. Experimental results applied for indoor and outdoor scenes showed the effectiveness of the proposed method.