Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
This paper describes a method for articulated upper body tracking in monocular scenes. The compatibility between model and the image is estimated using one particle filter for eac...
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...
We consider the problem of distributed classification of multiple observations of the same object that are collected in an ad-hoc network of vision sensors. Assuming that each sen...
IAPR Workshop on Machine Vision and Applications, pp. 455-458, 2000, Tokyo, Japan In this paper, we integrate the model-based tracking and local contexture (temporal and spatial) ...