Qingxuan Shi

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Vehicle tracking is an important part in intelligent transportation surveillance. But now vehicle tracking faces with the problems such as scale change, the interference of similar color, low resolution video data and so on. In this paper an improved Markov chain Monte Carlo(MCMC) named optical flow MCMC(OF-MCMC) sampling tracking algorithm is proposed for(More)
We address the problem of full body human pose estimation in video. Most previous work consider body part, pose or trajectory of body part as basic unit to compose the pose sequence. In contrast, we consider tracklet of body part as the basic unit. Based on this medium granularity representation we develop a spatio-temporal graphical model to select an(More)
Our goal is to estimate contour flow (the contour pairs with consistent point correspondence) from inconsistent contours extracted independently in two video frames. We formulate the contour flow estimation locally as a motion segmentation problem where motion patterns grouped from optical flow field are exploited for local correspondence measurement. To(More)
We present a novel method to estimate full-body human pose in video sequence by incorporating global motion cues. It has been demonstrated that temporal constraints can largely enhance the pose estimation. Most current approaches typically employ local motion to propagate pose detections to supplement the pose candidates. However, the local motion(More)
Dense point trajectories estimation is a challenging yet important problem due to its potential of supporting other fields, such as motion estimation, action recognition, etc. In previous work, dense motion trackers always estimate trajectories based on consecutive frames and ignore scene context prior, thereby suffering from inaccurate estimation. In this(More)
We propose a simple but effective tracking algorithm for non-rigid objects with geometric appearance changes. The discriminative features of the object are adaptively selected according to their descriptive ability. To adapt to the geometric changes, we use a deformable rectangle to represent the object, and use Markov Chain Monte Carlo-based Particle(More)
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