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Fundamental matrix estimation is the key technology in 3D reconstruction and widely used in many aspects in computer vision. In this paper, a global search genetic algorithm combining with a local search hill climbing algorithm is proposed to optimize MAPSAC algorithm for estimating fundamental matrix. The average distances between points and epipolar lines under noise and outliers are investigated...
In this paper, we propose a cascade dictionary learning algorithm for action recognition. In the first stage, a dictionary for basic sparse coding is learned based on local descriptors. And then spatial pyramid features are extracted to represent all the images in the same dimensions. Instead of performing dimension reduction, all the features are regrouped and then fed into second dictionary learning...
Recent work shows interest-point-based representation is greatly popular in action recognition, due to their simple implementation and good reliability. The neighborhood information of local descriptors usually improves the recognition accuracy. Taking inspiration from this observation, we propose a novel hierarchical neighborhood descriptor for action recognition. At low level, we propose the compound...
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