Integrating a Discrete Motion Model into GMM Based Background Subtraction

International audienceGMM based algorithms have become the de facto standard forbackground subtraction in video sequences, mainly becauseof their ability to track multiple backgrounddistributions, which allows them to handle complex scenesincluding moving trees, flags moving in the wind etc.However, it is not always easy to determine whichdistributions of the mixture belong to the background andwhich distributions belong to the foreground, whichdisturbs the results of the labeling process for eachpixel. In this work we tackle this problem by taking thelabeling decision together for all pixels of severalconsecutive frames minimizing a global energy functiontaking into account spatial and temporal relationships. Adiscrete approximative optical-flow like motion model isintegrated into the energy function and solved withIshikawa's convex graph cuts algorithm