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Disjoint inter-camera object tracking is the task of tracking objects across video-surveillance cameras that have non-overlapping views. Unlike the closely related task of single-camera tracking, disjoint inter-camera tracking is difficult due to the gaps in observation as an object moves between camera views. To overcome this problem, appearance profiles of the objects seen in each camera are built...
We present a real-time pedestrian detection system based on structure and appearance classification. We discuss several novel ideas that contribute to having low-false alarms and high detection rates, while at the same time achieving computational efficiency: (i) At the front end of our system we employ stereo to detect pedestrians in 3D range maps using template matching with a representative 3D...
An automatic object tracking technology is developed for a digital camera. We have developed a new modified object tracking algorithm based on K-means tracker algorithm that is adaptive to the change of the object shape and appearance. Several modifications for higher tracking performance and lower computation cost are introduced for the digital camera application.
A generic approach is presented to detect and track people with a network of fixed and omnidirectional cameras given severely degraded foreground silhouettes. The problem is formulated as a sparsity constrained inverse problem. A dictionary made of atoms representing the silhouettes of a person at a given location is used within the problem formulation. A reweighted scheme is considered to better...
Tracking and counting multiple humans in complex situations is challenging. The difficulties are tackled with appropriate knowledge in the form of various models in our approach. Human motion is decomposed into its global motion and limb motion. Multiple human objects were segmented and their global motions were tracked in 3D using ellipsoid human shape models. An improved method aiming to estimate...
Occlusion and lack of visibility in crowded and cluttered scenes make it difficult to track individual people correctly and consistently, particularly in a single view. We present a multi-view approach to solving this problem. In our approach we neither detect nor track objects from any single camera or camera pair; rather evidence is gathered from all the cameras into a synergistic framework and...
Object tracking methods based on stereo cameras, which provide both color and depth data at each pixel, find advantage in separating objects from each other and from background, determining the 3D size and location of objects, and modeling object shape. However, stereo tracking methods to date sometimes fail due to depth image noise, and discard much useful appearance information. We propose augmenting...
This paper proposes a novel approach to non-rigid, markerless motion capture from synchronized video streams acquired by calibrated cameras. The instantaneous geometry of the observed scene is represented by a polyhedral mesh with fixed topology. The initial mesh is constructed in the first frame using the publicly available PMVS software for multi-view stereo [7]. Its deformation is captured by tracking...
Here we propose the method for tracking of the selected object in video sequence in the absence of a-prior information about background evolution, as well as size and a form of an object. Under such conditions a contouring of an object has to be performed prior to a tracking. Maximum likelihood method is employed for efficient contouring. Estimation of likelihood function, based on residual functions...
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