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International Conference on Computer Vision (ICCV)

作者： Xiaowei Zhao Shiguang Shan Xiujuan Chai Xilin Chen Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology Beijing China

ISBN: (纸本)9781479928415

In this paper, we propose a novel cascaded face shape space pruning algorithm for robust facial landmark detection. Through progressively excluding the incorrect candidate shapes, our algorithm can accurately and efficiently achieve the globally optimal shape configuration. Specifically, individual landmark detectors are firstly applied to eliminate wrong candidates for each landmark. Then, the candidate shape space is further pruned by jointly removing incorrect shape configurations. To achieve this purpose, a discriminative structure classifier is designed to assess the candidate shape configurations. Based on the learned discriminative structure classifier, an efficient shape space pruning strategy is proposed to quickly reject most incorrect candidate shapes while preserve the true shape. The proposed algorithm is carefully evaluated on a large set of real world face images. In addition, comparison results on the publicly available BioID and LFW face databases demonstrate that our algorithm outperforms some state-of-the-art algorithms.

关键词： Shape Face Detectors Optimization Databases Robustness Detection algorithms

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Cross-view graph embedding

Cross-view graph embedding

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Huang, Zhiwu Shan, Shiguang Zhang, Haihong Lao, Shihong Chen, Xilin Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China OMRON Social Solutions Co. Ltd. Kyoto Japan

ISBN: (纸本)9783642374432

Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) under the proposed framework. Different from previous cross-view methods only preserving inter-view discriminant information or the intra-view local structure, CLODA preserves the local structure and the discriminant information of both intra-view and inter-view. Extensive experiments are conducted to evaluate our algorithms on two cross-view face recognition problems: face recognition across poses and face recognition across resolutions. These real-world face recognition experiments demonstrate that our framework achieves impressive performance in the cross-view problems. © 2013 Springer-Verlag.

关键词： Face recognition

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A Model of Three Points for Location Estimation in Wireless Sensor Networks

A Model of Three Points for Location Estimation in Wireless ...

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2013 2nd International Symposium on Materials Science and Engineering technology(ISMSET 2013)

作者： Shaoguo Xie Yanjun Hu Yi Wang Fang Jiang Jingjing Liu Yingguan Wang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education An Hui University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences

In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks(WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have the strongest received signal strength(RSS) for location estimation, the centroid algorithm and the method of intersection of judgment are used to estimate the location of unknown nodes. To further exploit three nearest intersection points in TP, the enhanced TP(ETP) is proposed. The simulation results show that the proposed models outperform MMSE and BML in terms of the localization accuracy for WSNs. Moreover, the localization accuracy of the proposed models in scenario 2 with random deployment of anchor nodes are better than in scenario 1 with planned deployment of anchor nodes. Additionally, compared with MMSE and BML, ETP and TP can reduce the environmental impact on location estimation.

关键词： Location estimation Anchor node Wireless sensor networks

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Nitrogen vertical distribution by canopy reflectance spectrum in winter wheat

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IOP Conference Series: Earth and Environmental Science 2014年第1期17卷

作者： W J Huang Q Y Yang D L Peng L S Huang D Y Zhang G J Yang Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100094 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 Anhui China Beijing Agriculture Information Technology Research Center Beijing 100097 China

Nitrogen is a key factor for plant photosynthesis, ecosystem productivity and leaf respiration. Under the condition of nitrogen deficiency, the crop shows the nitrogen deficiency symptoms in the bottom leaves, while excessive nitrogen will affect the upper layer leaves first. Thus, timely measurement of vertical distribution of foliage nitrogen content is critical for growth diagnosis, crop management and reducing environmental impact. This study presents a method using bi-directional reflectance difference function (BRDF) data to invert foliage nitrogen vertical distribution. We developed upper-layer nitrogen inversion index (ULNI), middle-layer nitrogen inversion index (MLNI) and bottom-layer nitrogen inversion index (BLNI) to reflect foliage nitrogen inversion at upper layer, middle layer and bottom layer, respectively. Both ULNI and MLNI were made by the value of the ratio of Modified Chlorophyll Absorption Ration Index to the second Modified Triangular Vegetation Index (MCARI/MTVI2) referred to as canopy nitrogen inversion index (CNII) in this study at ±40° and ±50°, and at ±30° and ±40° view angles, respectively. The BLNI was composed by the value of nitrogen reflectance index (NRI) at ±20° and ±30° view angles. These results suggest that it is feasible to measure foliage nitrogen vertical-layer distribution in a large scale by remote sensing.

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Benchmarking still-to-video face recognition via partial and local linear discriminant analysis on COX-S2V dataset

Benchmarking still-to-video face recognition via partial and...

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Huang, Zhiwu Shan, Shiguang Zhang, Haihong Lao, Shihong Kuerban, Alifu Chen, Xilin Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China OMRON Social Solutions Co. Ltd. Kyoto Japan College of Information Science and Engineering Xinjiang University China

ISBN: (纸本)9783642374432

In this paper, we explore the real-world Still-to-Video (S2V) face recognition scenario, where only very few (single, in many cases) still images per person are enrolled into the gallery while it is usually possible to capture one or multiple video clips as probe. Typical application of S2V is mug-shot based watch list screening. Generally, in this scenario, the still image(s) were collected under controlled environment, thus of high quality and resolution, in frontal view, with normal lighting and neutral expression. On the contrary, the testing video frames are of low resolution and low quality, possibly with blur, and captured under poor lighting, in non-frontal view. We reveal that the S2V face recognition has been heavily overlooked in the past. Therefore, we provide a benchmarking in terms of both a large scale dataset and a new solution to the problem. Specifically, we collect (and release) a new dataset named COX-S2V, which contains 1,000 subjects, with each subject a high quality photo and four video clips captured simulating video surveillance scenario. Together with the database, a clear evaluation protocol is designed for benchmarking. In addition, in addressing this problem, we further propose a novel method named Partial and Local Linear Discriminant Analysis (PaLo-LDA). We then evaluated the method on COX-S2V and compared with several classic methods including LDA, LPP, ScSR. Evaluation results not only show the grand challenges of the COX-S2V, but also validate the effectiveness of the proposed PaLo-LDA method over the competitive methods. © 2013 Springer-Verlag.

关键词： Benchmarking

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TEMPORALLY MULTIPLE DYNAMIC TEXTURES SYNTHESIS USING PIECEWISE LINEAR DYNAMIC SYSTEMS

TEMPORALLY MULTIPLE DYNAMIC TEXTURES SYNTHESIS USING PIECEWI...

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IEEE International Conference on Image processing

作者： Xing Yan Hong Chang Xilin Chen Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing 100190 China

ISBN: (纸本)9781479923427

Real-world nonlinear dynamic textures (DTs) usually consist of temporally multiple linear DTs which cannot be correctly modeled by previous works. In this paper, we propose piecewise linear dynamic systems (PLDS) to model temporally multiple DTs. PLDS simultaneously decides the temporal segmentation, models each DT segment with an LDS and the whole DT by switching between the LDS'. Experimental results verify that PLDS can capture the stochastic and dynamic nature of temporally multiple DTs and it synthesizes nonlinear DTs without decay or divergence. An EM-like algorithm iterating between sequence division and LDS' fitting is adopted to learn the model parameters.

关键词： Temporally Multiple Dynamic Textures Piecewise Linear Dynamic Systems Temporal Segmentation Local Digital Switch model parameters Programmable logic devices textures Stochastic dynamic decay Decay biodeterioration synthesis

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INSTANCE-SPECIFIC CANONICAL CORRELATION ANALYSIS FOR POSE ALIGNMENT

INSTANCE-SPECIFIC CANONICAL CORRELATION ANALYSIS FOR POSE AL...

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IEEE International Conference on Image processing

作者： Deming Zhai Hong Chang Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China 150001 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China 100080

ISBN: (纸本)9781479923427

Canonical correlation analysis (CCA) based methods achieve great success for pose alignment. However, CCA has limitations as a linear and global algorithm. Although some variants have been proposed to overcome the limitations, neither of them achieves locality and nonlinearity at the same time. In this paper, we propose a novel algorithm called Instance-Specific Canonical Correlation Analysis (ISCCA), which approximates the nonlinear data by computing the instance specific projections along the smooth curve of the manifold. Based on the framework of least squares regression, CCA is extended to the instance-specific case which obtains a set of locally-linear smooth but globally-nonlinear transformations. The optimization problem is proved to be convex and could be solved efficiently by alternating optimization. And the globally optimal solutions could be achieved with theoretical guarantee. Experimental results for pose alignment demonstrate the effectiveness of our proposed method.

关键词： proposed alignment transofrmations Alignment Posing optimal solution multivariate analysis nonlinearity Manifolds Convexity

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Sentimental Space Based Analysis of User Personalized Sentiments

Sentimental Space Based Analysis of User Personalized Sentim...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Xinzhi Wang Xiangfeng Luo School of Computer Engineering and Science Shanghai University Shanghai China Key Laboratory of Intelligent Information Processing Institute of Computing Technology hinese Academy of Sciences Beijing China

With the development of social media, online documents such as the comments of news articles, blogs and microblogs have received great attention, and the sentiment analysis via online documents has become one popular research area. This paper focuses on establishing user sentimental space obtained from online documents to analyze user's personalized sentiments, which aims to identify user's sentimental feature. Affection, sentiment and attributes of user are firstly employed to build user's personalized sentimental space. Then, the general constrains of user sentiments space are proposed to calculate user's personality. And finally we seek out sentimental leaders who paly pivotal role in the leading public opinions. Our works can give some suggestions for decision makers when urgent event happen.

关键词： Feature extraction Vectors Aerospace electronics Controllability Asymptotic stability Stability analysis Fluctuations

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Progressive Image Restoration through Hybrid Graph Laplacian Regularization

Progressive Image Restoration through Hybrid Graph Laplacian...

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Data Compression Conference (DCC)

作者： Deming Zhai Xianming Liu Debin Zhao Hong Chang Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Harbin Institute of Technology Harbin Heilongjiang CN

ISBN: (纸本)9781467360371

In this paper, we propose a unified framework to perform progressive image restoration based on hybrid graph Laplacian regularized regression. We first construct a multi-scale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space by exploring non-local self-similarity. In this procedure, the intrinsic manifold structure is considered by using both measured and unmeasured samples. On the other hand, between two scales, the proposed model is extended to the parametric manner through explicit kernel mapping to model the inter-scale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art image restoration algorithms.

关键词： Kernel Noise Image restoration Laplace equations Noise measurement Manifolds Linear programming

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Compressed sensing based on best wavelet packet basis for image processing

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Journal of Computers (Finland) 2013年第8期8卷 1947-1950页

作者： Li, Zhe Tao Xie, Jing Xiong Yu, Zu Guo Tu, Deng Biao Choi, Young June The College of Information Engineering Xiangtan University Hunan 411105 China School of Computer National University of Defense Technology Hunan 410073 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China School of Mathematics and Computational Science Xiangtan University Hunan 411105 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029 China Department of Information and Computer Engineering Ajou University Suwon 443749 Korea Republic of

In this paper, an algorithm named best wavelet packet tree decomposition (BWPTD) is proposed for image compression. In order to obtain better sparse representation of image, best wavelet packet basis is introduced to decompose image signal in the algorithm. Experimental results show that BWPTD is better than single layer wavelet decompression (SLWD) and original compressed sensing (OCS) in peak signal to noise ratio (PSNR) by 2db and 8db, respectively. In addition, the reconstruction time of BWPTD is only half as that of SLWD and OCS. © 2013 ACADEMY PUBLISHER.

关键词： Compressed sensing

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