In this paper, we propose a new technique to perform figure-ground segmentation in image sequences of moving objects under varying illumination conditions. Unlike most of the alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
— One of the fundamental problems of the mobile robots is self-localization, i.e. to estimate the self-position by comparing sensor data and a map. In non-stationary environments...
Kanji Tanaka, Tsutomu Hasegawa, Hongbin Zha, Eiji ...
— This paper proposes an approach allowing indoor environment supervised learning to recognize relevant features for environment understanding. Stochastic preprocessing methods i...
Abstract. A vision based head tracking approach is presented, combining foreground information with an elliptical head model based on the integration of gradient and skin-color inf...