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Yuan H.,Shandong University | Yuan H.,City University of Hong Kong | Yuan H.,CAS Shanghai Institute of Microsystem and Information Technology | Kwong S.,City University of Hong Kong | And 4 more authors.
IEEE Transactions on Circuits and Systems for Video Technology | Year: 2014

In three-dimensional videos (3-DV) coding systems, depth maps are not used for viewing but for rendering virtual views. Therefore, the traditional rate distortion criterion (including distortion criterion, and Lagrangian multiplier) is not suitable for depth map coding. In order to design an effective rate distortion criterion for depth maps, the relationship between the distortion of synthesized virtual view and the coding error of depth maps is analyzed in detail. Through the analysis, a polynomial model revealing the relationship between the coding error of depth maps and the distortion of synthesized virtual view is derived. Model parameters are estimated by utilizing camera parameters and features of the texture video corresponding to the depth map. Based on the model, a virtual view-based Lagrangian multiplier for depth map coding is also proposed. Experimental results demonstrated the accuracy of the model. The squared correlation coefficients between the actual distortion of virtual view and the estimated distortion are all larger than 0.98 for all tested sequences. When incorporating the proposed model and Lagrangian multiplier into the mode decision procedure of joint model version 18.5 (JM18.5) of H.264/AVC, a maximum 0.470 dB BD PSNR and an average 0.251 dB BD PSNR can be achieved. © 2014 IEEE.


Liang T.,Shandong University of Science and Technology | Fan J.,Shandong University of Science and Technology | Zhao J.,Shandong University of Science and Technology | Liang Y.,Shandong University of Science and Technology | Li Y.,Hisense State Key Laboratory of Digital Multi media Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Slope One predictor, an item-based collaborative filtering algorithm, is widely deployed in real-world recommender systems because of its conciseness, high-efficiency and reasonable accuracy. However, Slope One predictor still suffers two fundamental problems of collaborative filtering: sparsity and scalability, and its accuracy is not very competitive. In this paper, to alleviate the sparsity problem for Slope One predictor, and boost its scalability and accuracy, an improved algorithm is proposed. Through fuzzy clustering technique, the proposed algorithm captures the latent information of users thereby improves its accuracy, and the clustering mechanism makes it more scalable. Additionally, a high-accuracy filling algorithm is developed as preprocessing tool to tackle the sparsity problem. Finally empirical studies on MovieLens and Baidu dataset support our theory. © Springer-Verlag 2013.


Ge C.,Shandong University | Liu J.,Shandong University | Liu J.,Hisense State Key Laboratory of Digital Multi Media Technology | Yuan H.,Shandong University | Yuan H.,CAS Shanghai Institute of Microsystem and Information Technology
Journal of Electronic Imaging | Year: 2014

In three-dimensional video coding (3-DVC), it is reasonable to allocate different coding bits for multiview videos and associated depth maps because of their different characteristics to meet the bits' restraints of bandwidth/storage. We first propose a virtual view average distortion model. Then, based on the quantization parameter (QP), the average distortion-QP models and sum bitrate-QP models are proposed to depict the average distortions and sum bitrates of the referenced views for multiview videos and depth maps. Finally, the 3-DVC bit allocation problem is converted as a constrained optimization problem, which is solved by a genetic algorithm to search for the optimal QP pair. Experimental results demonstrate the effectiveness of our proposed models. Since the bit allocation scheme takes the performance of synthesized view and bitrate utilization into consideration, the absolute difference between the constraint and the actual coding bitrates (referred to as "rate inaccuracy") of the proposed method is only 7.405% on average, which greatly outperforms the fixed 5:1 ratio-based method with a rate inaccuracy of 19.103% and the planar model-based method with a rate inaccuracy of 20.556%. Compared with these two methods, our proposed method can achieve a maximum 1.951-dB gain under the same bitrates constraint. © 2014 SPIE and IS&T.


Lai C.,Harbin Institute of Technology | Lai C.,Shandong University | Liu J.,Shandong University | Liu J.,Hisense State Key Laboratory of Digital Multi Media Technology | And 2 more authors.
Journal of Medical Imaging and Health Informatics | Year: 2015

In image analysis, an image with a large number of pixels is often transformed into a reduced number of characteristic quantities referred to as features. This paper presents a feature extraction method for structural magnetic resonance imaging (sMRI) data of Alzheimer diseases. The method firstly employs an uncorrelated multilinear principal component analysis (PCA) to extract rough features from the tensorial sMRI data, and then applies a linear discriminant analysis to transform the features obtained by the uncorrelated multilinear PCA into a single feature identified to be most discriminative for classification of Alzheimer disease subjects from healthy controls. To evaluate the discrimination capability, a support vector machine is built to classify the two classes of subjects by the single feature. The proposed method has got higher classification accuracy than some competitive methods in our experiments. Copyright © 2015 American Scientific Publishers


Hu R.,Shandong University | Liu J.,Shandong University | Yuan H.,Shandong University | Ge C.,Shandong University | Liu W.,Hisense State Key Laboratory of Digital Multi Media Technology
Lecture Notes in Electrical Engineering | Year: 2014

Gray System Theory (GST) is employed to solve problems with less data, little sample, and insufficient experience, it has been successfully applied to medicine, industry technology, and so on. In this paper, a Gray Model (GM) based intra prediction method for H.264/AVC is proposed. For a certain block, when all the predicted values (obtained from the existing intra prediction methods) are similar, they are sent to a Gray system so as to obtain the final prediction results. Accordingly, the rate distortion decision procedure could be saved; meanwhile the mode information could also be saved. Since the encoder and decoder can determine whether different prediction results are similar or not, no additional flag information should be included into the bit-stream. Experimental results demonstrate that by integrating the GM-based prediction method into the H.264/AVC Joint Model version 15.1 (JM15.1), an average 2.994 % bit rate and 39.28 % coding time can be saved while maintaining the same quality of reconstructed videos. © Springer-Verlag Berlin Heidelberg 2014.


Wan W.,Shandong University | Liu J.,Shandong University | Liu J.,Hisense state key laboratory of digital multi media technology | Sun J.,Shandong University | And 2 more authors.
Multimedia Tools and Applications | Year: 2015

In the quantization-based watermarking framework, the perceptual just noticeable distortion (JND) model has been widely used to determine the quantization step size, as it can be used for the better tradeoff between imperceptibility and robustness. However, the calculated JND values will change as watermark embedding can affect the texture and luminance of the image. Consequently, the changes of JND values will lead to watermark-extraction errors. In this paper, the authors present an improved logarithmic spread transform dither modulation (STDM) watermarking approach using a best-matched DCT-based perceptual JND model, which can be insensitive to the changes caused by watermark embedding and attacks. Experimental results confirm the improved robustness performance of the JND model in the watermarking framework. Simulation results show that the proposed scheme is more robust than the existing JND model-based watermarking algorithms with the uniform fidelity, and our proposed scheme has a superior performance compared with the former proposed perceptual STDM schemes. © 2015 Springer Science+Business Media New York


Nie X.S.,Shandong University of Finance and Economics | Nie X.S.,Shandong University | Liu J.,Shandong University | Liu J.,Hisense State Key Laboratory of Digital Multi Media Technology | And 3 more authors.
Science China Information Sciences | Year: 2013

This study proposes a robust video hashing for video copy detection. The proposed method, which is based on representative-dispersive frames (R-D frames), can reveal the global and local information of a video. In this method, a video is represented as a graph with frames as vertices. A similarity measure is proposed to calculate the weights between edges. To select R-D frames, the adjacency matrix of the generated graph is constructed, and the adjacency number of each vertex is calculated, and then some vertices that represent the R-D frames of the video are selected. To reveal the temporal and spatial information of the video, all R-D frames are scanned to constitute an image called video tomography image, the fourth-order cumulant of which is calculated to generate a hash sequence that can inherently describe the corresponding video. Experimental results show that the proposed video hashing is resistant to geometric attacks on frames and channel impairments on transmission. © 2013 Science China Press and Springer-Verlag Berlin Heidelberg.


Cheng C.,Shandong University | Liu J.,Shandong University | Liu J.,Hisense State Key Laboratory of Digital Multi Media Technology | Yuan H.,Shandong University | And 2 more authors.
2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings | Year: 2013

Depth-image-based rendering (DIBR) has attracted more and more attention as a method of virtual view rendering in three-dimensional video (3DV) applications. Many efforts have been dedicated to realize high-quality rendering, ranging from pre-process of the reference depth images to post-process of the virtual texture images. A DIBR method based on inverse mapping and depth-aided image inpainting technique is proposed in this paper. In the proposed method, inverse mapping rendering technique is adopted to realize the 3D warping instead of traditional forward mapping; and a modified image inpainting technique in which depth information is considered is employed to inpaint the disocclusion regions. Besides, morphological processing is performed on the reference depth image to avoid the artifacts along the disocclusion areas. Experimental results demonstrate that the proposed method can obtain higher peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) in comparison to the previous methods, while producing satisfactory visual effect. © 2013 IEEE.


Hu R.,Shandong University | Yuan H.,Shandong University | Ge C.,Shandong University | Li Y.,Hisense State Key Laboratory of Digital Multi Media Technology | Liu W.,Hisense State Key Laboratory of Digital Multi Media Technology
WIT Transactions on Information and Communication Technologies | Year: 2014

A planar model based intra prediction method for depth map is proposed based on the analyses of the nature of depth maps. The neighboring pixels as well as their corresponding pixel coordinates of current block are utilized to compute model parameters. Then, the predicted pixels of the current block are calculated based on the proposed model. Finally, a rate distortion criterion is used to choose the optimal prediction method between the proposed one and those of H.264. Experimental results demonstrate that by implementing the proposed method into H.264/multi-view video coding (MVC) software platform Joint Model of Multi-view Video Coding version 8.3 (JMVC8.3), the maximum and average bit rate savings of depth maps can be achieved as high as -13.14% and -6.35%, respectively, while maintaining the same quality of synthesized virtual views. © 2014 WIT Press.


Wan W.,Shandong University | Liu J.,Shandong University | Liu J.,Hisense State Key Laboratory of Digital Multi Media Technology | Sun J.,Shandong University | And 3 more authors.
Electronics Letters | Year: 2015

Owing to the validity of measuring the visual visibility for image distortion, just noticeable distortion (JND) has been widely used in the quantisation-based watermarking framework. However, the existing JND model treats every region in the image with an equal attention level. Visual saliency, which reflects the visual attention, is proposed to improve the perceptual JND model. Based on the improved model, a logarithmic spread transform dither modulation (STDM) watermarking scheme is proposed. Simulations show that the proposed watermarking scheme with the improved JND model has superior robustness compared with existing STDM schemes. © The Institution of Engineering and Technology 2015.

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