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This paper describes a method of cross-domain object categorization, using the concept of domain adaptation. Here, a classifier is trained using samples from the source/auxiliary domain and performance is observed on a set of test samples taken from a different domain, termed as the target domain. To overcome the difference between the two domains, we aim to find a sequence of optimally weighted sub-spaces,...
Key frame based video summarization, which enables an user to access any video in a friendly and meaningful way, has emerged as an important area of research for the multimedia community. Various pattern clustering techniques are applied for the extraction of key frames from a video to form a storyboard. In this work, we improve existing Delaunay graph based video summarization framework with i) semantic...
This paper describes a method to solve the problem of Object-Centric Content Based Image Retrieval (CBIR), motivated by concepts from theory of cognitive sciences. According to cognitive models, there are two lobes in human brain, one is responsible to solve the problem of object recognition, while the other solves the problem of localization (or detection). It is the exchange of mutual information...
Too much irregularity in shapes of intraclass images poises an intrinsic challenge for recognition of handwritten alpha-numeric characters. We propose, in this paper, a perimetric complexity based handwritten numeral recognition that is inspired from gestalt configural superiority effect. A point-wise correspondence is obtained from the matching of shape context using affine transformation. A set...
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