Tracking and recognizing non-rigid objects in video image sequences are complex tasks of increasing importance to many applications. In this paper, we present a hierarchical reali...
SangKyu Kang, Joon Ki Paik, Besma R. Abidi, Yan Zh...
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
A robust video object segmentation algorithm for complex conditions in surveillance systems is proposed in this paper. This algorithm contains an unsupervised K-Means background c...
Abstract This paper proposes a Qualitative Normalised Templates (QNTs) framework for solving the human motion classification problem. In contrast to other human motion classifica...
Robust real-time tracking of non-rigid objects in a dynamic environment is a challenging task. Among various cues in tracking, color can provide an efficient visual cue for this t...