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Over the past two years deep convolutional neural networks have pushed the performance of computer vision systems to soaring heights on semantic segmentation. In this study, the authors present a novel semantic segmentation method of using a deep fully convolutional neural network to achieve image segmentation results with more precise boundary localisation. The above segmentation engine is trainable,...
Removal of visually unpleasant motion from videos is an important video enhancement technology. We present a feature-based approach for video stabilization that produces stabilized videos, while preserving the original resolution. To characterize the global/camera motion, SIFT features are extracted and carefully chosen to define the homography of 2D perspective warp between two consecutive frames...
In this paper, we propose a vision-based people counting system. The symmetry property of human torso is utilized for the detection of people. Using the symmetry property as feature, one can solve the incomplete extraction of human silhouette problem that is commonly encountered in the process of background subtraction. In addition, since the perspective projection effect may influence the orientation...
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