As environments become smart in accordance with advances in ubiquitous computing technology, researchers are struggling to satisfy users' diverse and sophisticated demands. Th...
Jin Choi, Yong-il Cho, Kyusung Cho, Su-jung Bae, H...
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
This paper proposes a system architecture for event recognition that integrates information from multiple sources (e.g., gesture and speech recognition from distributed sensors in...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...