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In the human body tracking based on video sequences, the pose estimation of the upper/lower limbs is the most challenging task since the limbs possess most variations of motions and are easily occluded. In this work, we present a sophisticated scheme to track the human limbs. First, the tracking is formulated as a constrained optimization problem with multiple kernels. The color features of the upper/lower...
Distributed camera networks have been deployed in the modern surveillance systems. The camera link model, including transition time distribution and brightness transfer function that represent the space-time relationship and color model between two cameras, is a critical element for tracking objects across the cameras. In this paper, we formulate the estimation of the camera link model as an optimization...
The purpose of ground truth data is to provide an absolute reference to be compared with algorithms' results. However, collecting ground truth data for real-life applications is an important but very disturbing task. This is particularly true for license plate recognition applications because of time-consuming manual. In this paper, we present a method of two-stage vehicle leaving and entering detection...
The appearance of one object may be seen differently from distinct cameras with overlapping views due to the color deviation and perspective difference. In this paper, we study these problems and propose an appearance modeling technique in order to perform the tracking across the multiple cameras. For single camera tracking, an effective integrated Kalman filter and multiple kernels tracking scheme...
Kernel based trackers have been proven to be a promising approach in video object tracking. The use of single kernel often suffers from occlusion since the visual information is not sufficient for kernel usage. Hence, multiple inter-related kernels have been utilized for tracking in complicated scenarios. This paper embeds the multiple kernels tracking into a Kalman filtering-based tracking system,...
This paper proposes a 3D human body pose reconstruction system based on videos captured from any perspective view of a monocular camera. The appearance, color and temporal information extracted from the video frames are effectively combined to accurately track 2D body features. This view invariant system overcomes the challenges of requiring the modeled human to be viewed from a pre-specified angular...
In surveillance applications, search space reduction (SSR) is an essential element to efficient algorithms. In this study, spatial and temporal SSRs are integrated for license plate detection in video sequences; the plates could be extracted robustly and extremely fast. Our method started from spatial SSR by a bi-level one-pass plate extraction (BOPE) algorithm developed to extract plates accurately...
Automatic visual tempo analysis and adaptive shot detection are studied for MTV-style home video authoring. Based upon the significant variation caused by object and background independently, spatial and temporal analysis are integrated for region of interest(ROI) detection in video sequences. To further detect homogeneous shots, visual tempos are proposed to describe the variation. Then, an adaptive...
Automatic authoring of MTV-style home video using visual and music tempo analysis is studied in this work. In the proposed system, the input home video is first segmented into shots by low level features such as the color histogram difference. Then, three types of tempo analysis are conducted; namely, music, global visual (the frame level) and local visual (the facial expression level) tempo analysis...
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