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The problem of simultaneously estimating affine deformations between multiple objects occur in many applications. Herein, a direct method is proposed which provides the result as a solution of a linear system of equations without establishing correspondences between the objects. The key idea is to construct enough linearly independent equations using covariant functions, and then finding the solution...
This paper presents the theory and applications of rectangular based binary image representation (RBIR). An automatic method is proposed to convert original binary image into RBIR. Some applications directly derived from RBIR are introduced. RBIR lossless compression is comparable with the run-length encoding (RLE) compression. Efficient algorithms are proposed for computing the dilation/erosion from...
We propose an integrated and personalized video retrieval and summarization system. We estimate and impose appropriate preference values on affinity propagation graph of the video frames. Then, our system produces the summary which is useful for the user in her/his relevance feedback and for the retrieval module for comparing video pairs. The experiments confirm the effectiveness of our approach for...
This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is...
A standard paradigm to apply graph based representations to computer vision and pattern recognition is to construct a graph from the problem and then formulate the problem in terms of finding cliques in the graph. Many methods have been proposed to extract maximum clique, enumerate all cliques or a number of largest cliques. In this paper we present an approach to a new problem of target clique extraction,...
In this paper we present a method to recover a spectra representation for reproduction and recognition on multispectral imagery. To do this, we commence by viewing the spectra in the image as a mixture which can be expressed in terms of the sample mean and a set of basis vectors and weights. This treatment leads to an MAP approach where the sample means is given by the centers yielded by the application...
This paper presents a new unsupervised statistical model for human activity discovery and recognition in pervasive environments. The activities are encoded in sequences recorded by non-intrusive sensors disseminated in the environment. Our model studies the relationship between the activities and the sequential patterns from the sequence analysis perspective. Activity discovery is formulated as an...
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