Abstract. This paper is concerned with algorithms for the logical generalisation of probabilistic temporal models from examples. The algorithms combine logic and probabilistic mode...
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on th...
In the analysis of natural images, Gaussian scale mixtures (GSM) have been used to account for the statistics of filter responses, and to inspire hierarchical cortical representat...
Odelia Schwartz, Terrence J. Sejnowski, Peter Daya...
Tracking multiple objects is important in many application domains. We propose a novel algorithm for multi-object tracking that is capable of working under very challenging conditi...