Appearance-Based Statistical Object Recognition by Heterogeneous Background and Occlusions

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