In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Reliable and efficient perception and reasoning in dynamic and densely cluttered environments are still major challenges for driver assistance systems. Most of today's system...
This paper presents a new technique for the perception of activities using statistical description of spatio-temporal properties. With this approach, the probability of an activit...
Abstract— Knowledge of the driving environment is essential for robotic vehicles to comply with traffic rules while autonomously traversing intersections. However, due to limite...
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...