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This paper describes a method for object detection and recognition based on appearance based approach. We introduce a probabilistic model to describe the wide variation of object appearance in images. In our method, objects are modeled as probabilistic features of silhouette and edge. These features are extracted from the object images viewed from various distance and orientation, and form the training...
Kernel principal component analysis (KPCA) has gained much attention for capturing nonlinear image features which is particularly important for clustering high-dimensional multi-class features. We introduce KPCA in this paper for detecting and classifying moving vehicles from its viewpoint images. The KPCA extracts non-linear features of multi-class moving vehicles by mapping input space to a higher...
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