Rastreamento de objetos usando descritores estatísticos - Dihl, Leandro Lorenzett (Universidade do Vale do Rio do Sinos, 2009)
The low cost of image acquisition systems and increase the computational power of available machines have caused a growing demand for automated video analysis in several applications, such as surveillance, human-computer interfaces, analysis of sports performance, etc. Object tracking through the video sequence is part of this analysis, and it has been a challenging problem in the computer vision area. This work presents a new approach for object tracking based on fragments. Initially, the region selected for tracking is divided into rectangular subregions (patches, or fragments), and each patch is tracked independently. Moreover, the motion history of the object is used to estimate its position in the subsequent frames. The overall displacement of the object is then obtained combining the displacements of each patch and the predicted displacement vector in order to priorize fragments presenting consistent displacement. An update scheme is also applied to the model, to deal with illumination and appearance c
Object tracking using statistical descriptors
Keywords: distância de Bhattacharyya; matrizes de covariância; múltiplos fragmentos; rastreamento de objetos; visão computacional; Bhattacharyya distance; covariance matrices; multiple fragments; object tracking; computer vision; Ciências Exatas e da Terra