A two-stage shot boundary detection framework in the presence of fast movements: Application to soccer videos

This paper addresses the shot boundary detection issue in soccer videos, in presence of fast camera and/or players movements. An approach is proposed based on the modified dissimilarity features corresponding to the distribution of intensity histogram of pixels as well as image texture combined with a fuzzy C-Mean clustering method. In the proposed approach, the singular value decomposition technique is used to map into the refined features space which considerably simplifies the detection process. As a key feature of the proposed approach, some preprocessing techniques are proposed to cope with the effects of fast movements in the videos. Furthermore, in the detection step a two-stage defuzzifier is introduced to increase the precision. Finally, the proposed method is applied to a big dataset which demonstrates its effectiveness and performance.