Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Object Recognition Using Multidimensional Receptive Field Histograms
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Discriminative Training of Gaussian Mixtures for Image Object Recognition
Mustererkennung 1999, 21. DAGM-Symposium
Dealing with occlusions in the eigenspace approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
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In this paper we present a new approach for the localization and classification of 2-D objects that are situated in heterogeneous background or are partially occluded. We use an appearance-based approach and model the local features derived from wavelet multiresolution analysis by statistical density functions. In addition to the object model we define a new model for the background and a function that assigns the single feature vectors either to the object or to the background. Here, the background is modelled as uniform distribution, therefore we need for all possible backgrounds only one density function. Experimental results show that this model is well suited for this recognition task.