This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
We present results on a user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS). The system automatically d...
Marian Stewart Bartlett, Gwen Littlewort, Mark G. ...
This paper proposes a mapping learning approach for caricature auto-generation. Simulating the artist’s creativity based on the object’s facial feature, our approach targets d...