Multi-step Multi-camera View Planning for Real-Time Visual Object Tracking

We present a new method for planning the optimal next view for a probabilistic visual object tracking task. Our method uses a variable number of cameras, can plan an action sequence several time steps into the future, and allows for real-time usage due to a computation time which is linear both in the number of cameras and the number of time steps. The algorithm can also handle object loss in one, more or all cameras, interdependencies in the camera’s information contribution, and variable action costs. We evaluate our method by comparing it to previous approaches with a prerecorded sequence of real world images. From K. Franke et al., Pattern Recognition, 28th DAGM Symposium, Springer, 2006, (pp. 536–545).