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This paper presents a novel approach to detecting the presence of objects in a scene from the 3D sparse disparity space obtained by stereo matching. The use of stereo imaging makes the proposed method particularly useful for detecting stationary objects without the need of learning the appearance patterns on an object or the background. Our approach is based on the fact that sparse image features...
This paper present a new image similarity measures for fast retrieving latent semantic similarity images via clustering feature descriptors of images and indexing images. The approaches used in this paper is hierarchical cluster which is used to segment the collection of the image feature from image database and locality sensitive hashing which is used to index the similarity images. The proposed...
High-precision localization is one of the important applications in the field of computer vision. In this paper a high-precision template localization algorithm based on SIFT (scale invariant feature transform) is presented. The proposed method is composed of three main steps. In the initial step the SIFT features are extracted. With these features the basic matching strategy and clustering method...
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