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Wang Y.,Hisilicon Technologies | Luo X.,Shanghai JiaoTong University | Hu S.,Shanghai JiaoTong University
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2016

We propose an online tracking algorithm in which the object tracking is achieved by using subspace learning and non-negative matrix factorization (NMF) under the partile filtering framework. The object appearance is modeled by a non-negative combination of non-negative components learned from examples observed in previous frames. In order to robust tracking an object, group sparsity constraints are included to the non-negativity one. In addition, the Alternating Direction Method of Multipliers (ADMM) algorithm is proposed for efficient model updating. Qualitative and quantitative experiments on a variety of challenging sequences show favorable performance of the proposed algorithm against 9 state-of-the-art methods. © 2016 IEEE. Source


He Z.,Zhejiang University | Yu L.,Zhejiang University | Zheng X.,Hisilicon Technologies | Ma S.,Peking University | He Y.,Tsinghua University
2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings | Year: 2013

The first generation of Audio-video coding standard (AVS1) will become an international standard of IEEE (IEEE.1857). The second generation of Audio-video coding standard (AVS2) is a successor to IEEE.1857 which targets to higher coding efficiency, especially for high resolution videos, with reasonable complexity increase. Currently, AVS2 working draft is developed, in which symbolic techniques of IEEE.1857, such as logarithmic arithmetic coding, are still used. It also introduces new coding tools, e.g. flexible partition structure which is based on macro-block structure and high efficient prediction methods utilizing more texture information and temporal redundancies, etc. The performance of AVS2 is improved by 37% compared to the IEEE.1857 Jiaqiang Profile and 16.4% compared to H.264 in average. This paper provides an overview of the framework of AVS2-video coding standard. © 2013 IEEE. Source


Wang Y.,Hisilicon Technologies | Luo X.,Shanghai JiaoTong University | Hu S.,Shanghai JiaoTong University
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2016

In this paper, we cast tracking as a novel multi-task learning problem and exploit various types of visual features. We use an on-line feature selection mechanism based on the two-class variance ratio measure, applied to log likelihood distributions computed with respect to a given feature from samples of object and background pixels. The proposed method is integrated in a particle filtering framework. We jointly consider the underlying relationship across different particles, and tackle it in a unified robust multi-task formulation. We show that the proposed formulation can be efficiently solved using the Alternating Direction Method of Multipliers (ADMM) with a small number of closed-form updates. Both the qualitative and quantitative results demonstrate the superior performance of the proposed approach compared to several state of-the-art trackers. © 2016 IEEE. Source


Zheng X.,Hisilicon Technologies | Zheng J.,Hisilicon Technologies | He Y.,Tsinghua National Laboratory for Information Sciences and Technology
2012 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012 | Year: 2012

At current video coding layer, video data can be divided into different coding layers, e.g. sequence, picture, slice and macroblock. A coding layer contains same properties of video data. At slice layer, a certain amount of macroblocks are grouped to a slice, and coded as raster order within the slice. The slice structure can be used at rate control, error resilience and video transmission areas. Base on the concept of slice, the slice structure is extended at this paper. A so-called slice set structure groups slices that have some same properties together. The slices within a slice set can share and exchange data. Due to this superior feature, the proposed slice set structure can be used at ROI coding, and further improve error resilience capability © 2012 IEEE. Source


Zheng X.,Hisilicon Technologies | Li W.,Tsinghua National Laboratory for Information Sciences and Technology | Zheng J.,Hisilicon Technologies | Chen X.,Hisilicon Technologies
2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014 | Year: 2014

Depth map is a kind of video clip that contains 3D object's depth information, and is an important coding feature in the recently 3D video coding standards, which has been applied for the latest 3D coding approaches, e.g. MV-HEVC and 3D-HEVC. It has been approved that the support of depth map coding can significantly improve the coding performance for 3D videos, and provide more flexibility for 3D applications. Some previous works show that depth map has some different coding properties compared to the traditional 2D sequences. Many coding tools have different performance influence and behaviors on these two kind of video clips. This paper concentrates on the investigation and analysis of those phenomena for depth map coding. © 2014 Asia-Pacific Signal and Information Processing Ass. Source

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