Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
— In this work, we have extended the concept of constrained motion control of robots to surgical tasks that require multiple robots. We present virtual fixtures to guide the mot...
To cope with the explosive increase in the number of requests to Internet server systems, one popular solution is a load-balancing technique that uses a dispatcher in the front-en...
We present an algorithm for interactive hair rendering with both single and multiple scattering effects under complex environment lighting. The outgoing radiance due to single sca...
Zhong Ren, Kun Zhou, Tengfei Li, Wei Hua, Baining ...
In this paper we rst describe how we have constructed a 3D deformable Point Distribution Model of the human hand, capturing training data semi-automatically from volume images via...