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Visual surveillance using multiple cameras has attracted increasing interest in recent years. Correspondence between multiple cameras is one of the most important and basic problems which visual surveillance using multiple cameras brings. In this paper, we propose a simple and robust method, based on principal axes of people, to match people across multiple(More)
—Occlusion reasoning is one of the most challenging issues in visual surveillance. In this letter, we propose a new approach for reasoning about occlusions between multiple people. In our approach, occlusion relationships between people are explicitly defined and deduction of the occlusion relationships is integrated into the whole tracking framework. The(More)
In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of(More)
Object tracking using active contours has attracted increasing interest in recent years due to acquisition of e«ective shape descriptions. In this paper, an object tracking method based on level sets using moving cameras is proposed. We develop an automatic contour initialization method based on optical flow detection. A Markov Random Field (MRF)-like model(More)
Conventional contour tracking algorithms with level set often use generative models to construct the energy function. For tracking through cluttered and noisy background , however, a generative model may not be dis-criminative enough. In this paper we integrate the dis-criminative methods into a level set framework when constructing the level set energy(More)
Dynamical shape priors are curical for level set-based non- rigid object tracking with noise, occlusions or background clutter. In this paper, we propose a level set tracking framework using dynamical shape priors to capture contours changes of an object in a periodic action sequence. The framework consists of two stages - off-line training and on-line(More)
In this paper, we propose a superpixel-driven method for level set tracking. In particular, by taking a superpixel-based speed function, the level set evolution is accelerated greatly. We define a mutual information based speed function using a superpixel-unit as the underlying representation, which captures the correlation of a superpixel with(More)
In an 802.11 wireless network with multiple access points (APs), for a commercial user, a prime concern is how to discover the desired AP since the AP providers maybe selfish and owned by different organization. This paper presents a generic reputation based framework for AP selection for this case. An M/M/1 queuing model is introduced to get a quantitative(More)
In consideration of the problem that the existing face recognition methods cannot handle the face recognition under unsatisfactory situations, such as shadows, occlusions, stains, which cause low recognition rate. Therefore, an algorithm based on discriminative low-rank matrix recovery with sparse constraint (DLRRSC) is proposed. First, discriminative(More)