We propose a framework for “probabilistic functional testing.” The success of a test data set generated according to our method guarantees a certain level of confidence into ...
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
We propose a Bayesian framework for representing and recognizing local image motion in terms of two primitive models: translation and motion discontinuity. Motion discontinuities ...
Generating vehicle trajectories from video data is an important application of ITS (Intelligent Transportation Systems). We introduce a new tracking approach which uses model-base...