In this paper, we propose a method of object recognition and segmentation using Scale-Invariant Feature Transform (SIFT) and Graph Cuts. SIFT feature is invariant for rotations, s...
Object recognition, i. e. classification of objects into one of several known object classes, generally is a difficult task. In this paper we address the problem of detecting an...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Due to distortion, noise, segmentation errors, overlap, and occlusion of objects in digital images, it is usually impossible to extract complete object contours or to segment the ...
Object recognition forms a ubiquitous problem in digital image processing. The detection of robust image features of high distinctiveness is one important key in this regard. We p...