Object detectors are typically trained on a large set of still images annotated by bounding-boxes. This paper introduces an approach for learning object detectors from realworld w...
Alessandro Prest, Christian Leistner, Javier Civer...
In this paper, we present a novel approach for extracting silhouettes by using a particular pattern that we call the random pattern. The volume intersection method reconstructs th...
In this paper, we present an efficient and robust subspace learning based object tracking algorithm with special illumination handling. Illumination variances pose a great challen...
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Abstract. This paper describes a color region-based approach to motion estimation in color image sequences. The system is intended for robotic and vehicle guidance applications whe...