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Abstract-Computer vision techniques such as Structurefrom- Motion (SfM) and object recognition tend to fail on scenes with highly reflective objects because the reflections behave differently to the true geometry of the scene. Such image sequences may be treated as two layers superimposed over each other - the nonreflection scene source layer and the reflection layer. However, decomposing the two...
The emergence of cloud datacenters enhances the capability of online data storage. Since massive data is stored in datacenters, it is necessary to effectively locate interest data in such a distributed system. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These techniques cannot satisfy the requirements of content based...
Traditional image stitching methods represented by SIFT are sensitive to non-linear illumination changes. In this paper, a new algorithm is presented for image stitching based on local symmetry features. Firstly, feature points are extracted using the detector based on local symmetry. Secondly, SIFT descriptor and local symmetry descriptor are combined to characterize those feature points. Thirdly,...
Accurate, real-time as well as high fitness of face detection is always the difficult problem of Face Recognition System. The paper aiming at the problem come up with a solution which can extract key frames of face from the video sequence. The algorithm using skin color and AdaBoost face detection to construct a real-time, high-efficient face key frames extractor. It can reduce AdaBoost cascade classifier...
Improved Pseudo-Zernike Moment (PZM) and artificial neural network (ANN) was combined within the hybrid architecture for face recognition. Improved PZM was used to extract face feature, and encoded to form the input vector sending to ANN. Experimental results demonstrate the present approach taking advantage of ANN, basically eliminates the effects of the change of face scale and rotation, and has...
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