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Locally Assembled Binary (lab) Feature with Feature-centric Cascade for Fast and Accurate Face Detection

Locally Assembled Binary (LAB) Feature with Feature-centric ...

引用

26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), vol.11

作者： Shengye Yan Shiguang Shan Xilin Chen Wen Gao Key Lab of Intelligent Information Processing Chinese Academy and Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy of Sciences (CAS) Beijing China School of EE& Peking University Beijing China Digital Media Research Center Institute of Computing Technology Chinese Academy and Sciences Beijing China

In this paper, we describe a novel type of feature for fast and accurate face detection. The feature is called Locally Assembled Binary (lab) Haar feature. lab feature is basically inspired by the success of Haar feature and Local Binary Pattern (LBP) for face detection, but it is far beyond a simple combination. In our method, Haar features are modified to keep only the ordinal relationship (named by binary Haar feature) rather than the difference between the accumulated intensities. Several neighboring binary Haar features are then assembled to capture their co-occurrence with similar idea to LBP. We show that the feature is more efficient than Haar feature and LBP both in discriminating power and computational cost. Furthermore, a novel efficient detection method called feature-centric cascade is proposed to build an efficient detector, which is developed from the feature-centric method. Experimental results on the CMU+MIT frontal face test set and CMU profile test set show that the proposed method can achieve very good results and amazing detection speed.

关键词： Assembly Face detection Computer vision Detectors Content addressable storage Computational efficiency Testing intelligent robots Humans Skin

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People re-detection using Adaboost with sift and color correlogram

People re-detection using Adaboost with sift and color corre...

引用

IEEE International Conference on Image processing

作者： Lei Hu Shuqiang Jiang Qingming Huang Wen Gao Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media Peking University Beijing China

People re-detection aims at performing re-identification of people who leave the scene and reappear after some time. This is an important problem especially in video surveillance scenarios. In this paper, we present a method of people re-detection within the context of visual sequence in single-camera setup. We consider re-detection as a binary classification problem, where both global and local descriptors are employed for training strong classifier on-line with adaboost to distinguish a newly detected people as tracked or new occurrence. The strong classifier will be updated while match is ascertained. A predetermined classifier with well-chosen threshold is employed as assistant of training examples collection. We test the performance of our approach on 4 different scenes including 51 video sequences taken from the CAVIAR database and 4 video sequences shot by ourselves. The results show that our re-detection algorithm can robustly handle variations in illumination, pose, scale, and camera-view.

关键词： Cameras Layout Surveillance Color Video sequences Data mining Joining processes Histograms information processing Computers

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Manifold-Manifold Distance with Application to Face Recognition based on Image Set

Manifold-Manifold Distance with Application to Face Recognit...

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26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), vol.9

作者： Ruiping Wang Shiguang Shan Xilin Chen Wen Gao Graduate School of Chinese Academy of Sciences Beijing China Digital Media Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy and Sciences Beijing China School of EE&CS Peking University Beijing China

In this paper, we address the problem of classifying image sets, each of which contains images belonging to the same class but covering large variations in, for instance, viewpoint and illumination. We innovatively formulate the problem as the computation of Manifold-Manifold Distance (MMD), i.e., calculating the distance between nonlinear manifolds each representing one image set. To compute MMD, we also propose a novel manifold learning approach, which expresses a manifold by a collection of local linear models, each depicted by a subspace. MMD is then converted to integrating the distances between pair of subspaces respectively from one of the involved manifolds. The proposed MMD method is evaluated on the task of Face Recognition based on Image Set (FRIS). In FRIS, each known subject is enrolled with a set of facial images and modeled as a gallery manifold, while a testing subject is modeled as a probe manifold, which is then matched against all the gallery manifolds by MMD. Identification is achieved by seeking the minimum MMD. Experimental results on two public face databases, Honda/UCSD and CMU MoBo, demonstrate that the proposed MMD method outperforms the competing methods.

关键词： Face recognition Probes Image converters Content addressable storage Testing Cameras Image storage Video sequences Image recognition Object recognition

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Algebra and calculus of the resource space model

Algebra and calculus of the resource space model

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3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007

作者： Xing, Yunpeng Zhuge, Hai Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)0769530079

Resource Space Model (RSM) is a semantic model to manage resources in the future interconnection environment. The query capability is an important aspect of RSM as a semantic resource management model. This paper reports the research result on the query capability of RSM from two perspectives: resource space algebra and resource space calculus. The equivalence of the resource space algebra and the resource space calculus has been discussed. © 2007 IEEE.

关键词： Algebra

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EFFICIENT IMAGE CLUSTERING USING A NEW IMAGE DISTANCE

EFFICIENT IMAGE CLUSTERING USING A NEW IMAGE DISTANCE

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： SU-LAN ZHANG QING HE ZHONG-ZHI SHI Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of

A new distance for image clustering called Generalized Geodesic Distance (GGD) and an appearance-based image clustering approach called Global Geometric Clustering for Image (GGCI) are *** the traditional distance, GGD takes into account the spatial relationships of ***, it is robust to small perturbation of *** based on GGD uses easily measured local metric information to learn the underlying global geometry of images space, then applies the extended nearest neighbor approach to cluster *** from the usual nearest neighbor approach, GGCI considers the density around the nearest points within manifolds embedded in high dimensional image space, which better reflects the intrinsic geometric structure of *** results suggest that the proposed GGCI approach achieves lower error rates in image clustering.

关键词： Geodesic distance Manifold Image clustering

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An authorization mechanism for resource space model

An authorization mechanism for resource space model

引用

3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007

作者： Zhu, Yuan Xing, Yunpeng Hunan Knowledge Grid Lab. Hunan University of Science and Technology Hunan China China Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100080 Beijing China

ISBN: (纸本)0769530079

Authorization mechanism is an effective technique of access control. In this paper, we construct a multidimensional authorization space for RSM with the guidance of the methodology of RSM design. This authorization space permits both positive and negative authorizations and supports exceptions and strong enforcement as well as the temporal constraints on the authorizations. For the sake of efficiency and convenience we extend the representation of object in GRANT command. © 2007 IEEE.

关键词： Authorization

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Urban road network extraction from SAR image

Urban road network extraction from SAR image

引用

MIPPR 2007: Remote Sensing and GIS Data processing and Applications;and Innovative Multispectral Technology and Applications

作者： Cheng, Pengxue Hu, Maolin Lab. of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469540

In this paper, a technique for the extraction of roads in a high resolution synthetic aperture radar (SAR) image is presented. And a three-step method is developed for the extraction of road network from space borne SAR image: the process of the feature points, road candidate detection and connection. Roads in a high resolution SAR image can be modeled as a homogeneous dark area bounded by two parallel boundaries. Dark areas, which represent the candidate positions for roads, are extracted from the image by a Gaussian probability iteration segmentation. Possible road candidates are further processed using the morphological operators. And the roads are accurately detected by Hough Transform, and the extraction of lines is achieved by searching the peak values in Hough Space. In this process, to detect roads more accurately, post-processing, including noisy dark regions removal and false roads removal is performed. At last, Road candidate connection is carried out hierarchically according to road established models. Finally, the main road network is established from the SAR image successfully. As an example, using the ERS-2SAR image data, automatic detection of main road network in Shanghai Pudong area is presented.

关键词： Feature extraction

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Point matching of two images under large different resolution

Point matching of two images under large different resolutio...

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MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition

作者： Ruan, Lei Hu, Maolin Lab. of Intelligent Computing and Signal Processing AnHui University Hefei AnHui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469502

Image matching is the first step in almost any 3D computer vision task, and hence has received extensive attention. In this paper, the problem is addressed from a novel perspective, which is different from the classic stereo matching paradigm. Two images with different resolutions, that is high resolution versus low resolution are matched. Since the high resolution image only corresponds to a small region of the low resolution one, the matching task therefore consists in finding a small region in the low resolution image that can be assigned to the whole high resolution image under the plane similarity transformation, which can be defined by the local area correlation coefficient to match the interest points and rectified by similarity transform. Experiment shows that our matching algorithm can be used for scale changing up to a factor of 6. And it is successful to deal with the point matching between two images under large scale.

关键词： Image matching

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A flexible stem-based local search algorithm for predicting RNA secondary structures including pseudoknots

A flexible stem-based local search algorithm for predicting ...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Chen, Xiang He, Si-Min Bu, Dong-Bo Chen, Run-Sheng Gao, Wen Key Lab. of Intelligent Information Processing Chinese Academy of Sciences Beijing 100080 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Insitute of Biophysics Chinese Academy of Sciences Beijing 100101 China Graduate University Chinese Academy of Sciences Beijing 100039 China

ISBN: (纸本)1424415098

We demonstrate a new algorithm named FlexStem to predict RNA secondary structures with pseudoknots. Our approach is based on the free energy minimization criterion, and utilizes a sophisticated energy model that is more accurate and supports more types of pseudoknots. By using a "maximal stem" and "stem merging" strategy, the search space for RNA structure prediction is significantly reduced. We have also developed a greedy search algorithm with perturbation on stems. The FlexStem algorithm is applied to a large number of sequences taken from Sprinzl, Pseudobase and other reliable resource. We find that FlexStem outperforms the well-known optimal and heuristic algorithms such as Mfold, PKNOTS, HotKnots and ILM in overall sensitivity and has comparable results to those algorithms in overall specificity. Performance evaluation demonstrate that FlexStem requires significantly less time than the optimal algorithm PKNOTS. In addition, our algorithm has better prediction results on pseudoknot-free sequences compared to competing algorithms. ©2007 IEEE.

关键词： Heuristic algorithms

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Algebra and Calculus of the Resource Space Model

Algebra and Calculus of the Resource Space Model

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2007年第三届语义和知识网格国际会议(Third International Conference on Semantics,Knowledge,and Grid)(SKG 2007)

作者： Yunpeng Xing Hai Zhuge China Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

关键词： Algebra Calculus Resource management Space technology Environmental management Ontologies Database languages information processing Computers Conference management

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