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Weighted prediction (WP) is an efficient tool for encoding of video with brightness variations, if WP parameters can be estimated accurately. In this paper, an improved estimation method for WP parameters of advanced video coding system (AVS) is proposed. To find a best matching block in reference for current block to be encoded, a motion search scheme is presented. Each block in a searching window...
Human action recognition in video sequences is an important research topic in computer vision, and motion history image (MHI) is widely taken for recognition due to its simplicity. However, it may be not robust to describe an action by only a single MHI. Therefore, an action recognition scheme by using multiple key MHIs (MKMHIs) is proposed. Firstly, an adaptive method for key MHIs selection is proposed...
In this paper, the wideband Capon cepstrum weighted l2, 1 minimization algorithm (WB-CW l2, 1) is presented for wideband direction of arrival (DOA) estimation using an acoustic array. The problem of wideband DOA estimation is converted into the estimation of the sparsity pattern of a jointly sparse signal and then solved by the weighted l2, 1 norm minimization. WB-CW l2, 1 uses the Capon cepstrum...
Kalman filtering is widely used in target tracking. However, conventional Kalman filtering may fail to track the target when there is acceleration, deceleration, and turn. In this paper, these maneuvers are characterized by two orthogonal components of the changed velocity in l1-norm. The adaptive factors to adjust the Kalman gain are then generated through a mapping function based on the characterization...
In the intra coding of HEVC/H.265, the computational complexity of intra mode decision is very high because up to 35 intra prediction modes are supported. Though a fast intra mode decision based on rough mode decision (RMD) is adopted in reference software HM12.0, only a fixed number of intra modes are selected for rate distortion optimization (RDO). In this paper, an adaptive fast intra mode decision...
Gradient domain optimization is widely used in regularized image super-resolution, in which the gradient of high resolution (HR) is estimated for calculating the regularization energy. In this paper, a progressive gradient estimation (PGE) is proposed. In PGE, the gradient of the reconstructed HR image in the previous round of optimization is taken as the estimated gradient in the current round. Then,...
This paper aims at optimizing the efficiency of the sparse representation based classification (SRC) method in automatic recognition, which is a common problem with large quantity of sample images. An automated target recognition framework based on SRC method is proposed through fast locating to the region of interest (ROI) and dictionary filtering meanwhile. We solve the alignment problem through...
In recent years, sparse representation-based classification (SRC) has received significant attention for its high recognition rate. However, the original SRC method requires rigid alignment. By further considering the robustness of scale and affine in this paper, we explore the relationship of the similarity of the SIFT descriptors to a recognition task and propose a clustering-weighted SIFT-based...
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