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Learning Multiple Pooling Combination for image Classification

Learning Multiple Pooling Combination for Image Classificati...

引用

International Joint Conference on Neural Networks

作者： Junlin Hu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)9781467314886

Recently sparse coding with spatial pyramid matching method has shown its excellent performance in image classification. Inspired by this technique, we present an image classification approach by learning the optimal Multiple Pooling Combination strategy based on Non-Negative Sparse Coding (MPC-NNSC) in this paper. First, non-negative sparse coding with three different pooling methods as well as spatial pyramid matching method are utilized to encode local descriptors for image representation, respectively. Then a promising weight learning approach is employed to find a set of optimal weights for best fusing all these pooling methods in different scales. Lastly, support vector machine classifier with linear and histogram intersection kernel is employed for the final classification task. Experiments on two popular benchmark datasets are presented and they demonstrate the better performance of the proposed scheme compared to the state-of-the-art methods.

关键词： image classification pooling Sparse coding image representation Nonnegative Pyramid

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image Segmentation Based on Visual Perception Model

Image Segmentation Based on Visual Perception Model

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2012年计算机应用与系统建模国际会议

作者： Shuai Shao Fuqing Duan Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University

image segmentation is the basis of image processing and image analysis. However, there are no common method that can be used in natural images, and present methods fail to explain understandings of human's visual system. In this paper, we propose to apply Karklin's visual perception model to extract feature vectors of images, and the features are clustered with K-means method. The results obtained in feature space are projected back to the image space to finish segmentation. A comparison with the Normalized Cuts (Ncut) method is done, and it turns out that proposed method outperform Ncut in texture rich images.

关键词： Visual perception model image segmentation Normalized cuts Feather extraction

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A Multiple Scattering in Participating Media for Real Time Rendering

A Multiple Scattering in Participating Media for Real Time R...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Ping Guo Yuanlong Wang Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)9781467317139

At present, multiple scattering problems in participating media is still very challenging for real time rendering. Some methods have proposed to describe multiple scattering phenomena, however, there are some restriction conditions such as requiring the medium is static, etc., and rendering speed is not satisfied real-time requirement. In order to speed up the multiple scattering rendering, we propose a GPU based algorithm in this paper. First of all, the media is initialized with a particle system and the property of each particle is defined;secondly, according to the properties of each particle, a method of tracing the particle path, which is generated by uniformly sampling the surrounding particles of one particle, is proposed and this method is used to compute in-scattering radiance for each particle;finally, the total radiance is calculated by summing up contributions of particles along ray paths and the final image is rendered. The experimental results show that the proposed algorithm can achieve the real-time rendering effect.

关键词： Component Computer graphics Ray tracing Multiple scattering Real tint e rendering Parallel computing Rendering broadcasting Scattering Ray paths particles radiance Real time

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Improved PSO algorithm with harmony search for complicated function optimization problems

Improved PSO algorithm with harmony search for complicated f...

引用

9th International Symposium on Neural Networks, ISNN 2012

作者： Yu, Jian Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China College of Mathematics and Information Technology Hanshan Normal University Chaozhou Guangdong 521041 China

ISBN: (纸本)9783642313455

Improved particle swarm optimization algorithm with harmony search (IHPSO) is proposed in this paper. This algorithm takes particle swarm search direction estimation mechanism and harmony search (HS) approach to particle swarm optimization (PSO) algorithm, which increases the search capability of PSO algorithm considerably. The proposed algorithm initializes a new search with harmony pitch adjusting or random selection when PSO search direction is estimated incorrectly. This can provide further opportunities of finding better solutions for the particle swarm by guiding the entire particle swarm to promising new regions of the search space and accelerating the search. PSO, HPSO and IHPSO, as well as other advanced PSO procedures from the literature were compared on several benchmark test functions extensively. Statistical analyses of the experimental results indicate that the performance of IHPSO is better than the performance of PSO and HPSO. © 2012 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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A hierarchical framework for image-based human age estimation by weighted and OHRanked Sparse Representation-based classification

A hierarchical framework for image-based human age estimatio...

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2012 5th IAPR International Conference on Biometrics, ICB 2012

作者： Li, Weixin Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781467303941

Human age estimation based on face images can figure in a wide variety of real-world applications. In this paper, we propose a novel and efficient facial age estimation algorithm which decides human age in a hierarchical framework. Biologically, human lives can be roughly divided into two stages, the period from birth to adulthood and the period from adulthood to old age, which are quite different from each other in face growth and aging forms. Considering that craniofacial growth occurs mainly in the first stage while keeps basically stable in the second, based on the shape features, the coarse step of the framework determines which age stage the test sample belongs to using a quadratic function. On the other hand, since the face appearance of individuals in the same age group or even of the same age does have some similarities in common, accurate age estimation within the age stage is solved by Sparse Representation-based classification (SRC) in the fine step. However, SRC requires sufficient training samples in each class and in practice this assumption often does not hold, making the performance of age estimation limited. Accordingly, we take use of the idea of Ordinal Hyperplanes Ranker (OHRank) and weights of samples' numbers in each class to solve the aforementioned problem, improving the age estimation results. Results of experiments conducted on the FG-NET Database demonstrate the effectiveness of our method. © 2012 IEEE.

关键词： image classification

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Ethnicity classification based on fusion of face and gait

Ethnicity classification based on fusion of face and gait

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2012 5th IAPR International Conference on Biometrics, ICB 2012

作者： Zhang, De Wang, Yunhong Zhang, Zhaoxiang Hu, Maodi Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781467303941

The recognition of ethnicity of an individual can be very useful in a video-based surveillance system. In this paper, we propose a multimodal biometric system involving an integration of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs a feature fusion to improve the discrimination of human ethnicity. Face features are extracted by means of the uniform LBP operator and gait information is characterized by a spatio-temporal representation. Afterwards, canonical correlation analysis (CCA), as a powerful tool to relate two sets of measurements, is used to fuse the two modalities at the feature level. A database including 36 walking people from East Asia and South America is built for the purpose of ethnicity classification. The experimental results show that the ethnicity recognition rate is improved by fusing face and gait information. © 2012 IEEE.

关键词： Classification (of information)

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Ethnicity classification based on a hierarchical fusion

Ethnicity classification based on a hierarchical fusion

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7th Chinese Conference on Biometric recognition, CCBR 2012

作者： Zhang, De Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9783642355059

In this paper, we propose a cascaded multimodal biometrics system involving a fusion of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs human ethnicity classification first from the cues of gait recorded by a long-distance camera and requires next classification using facial images captured by a short-distance camera only when gait based ethnicity identification fails. For gait, we use Gait Energy image (GEI), a spatio-temporal compact representation of gait in video, to characterize human walking properties. For face, we extract the well-known Gabor feature to render the effective facial appearance information. Experimental results obtained from a database of 22 subjects containing 12 East-Asian and 10 South-American shows that this cascaded system is capable of providing competitive discriminative power on ethnicity with a correct classification rate over 95%. © 2012 Springer-Verlag.

关键词： Classification (of information)

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Detection of billet character in complex production line scene

Detection of billet character in complex production line sce...

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2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012

作者： Hong, Hanyu Yu, Zhejun Zhang, Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547725

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application. © 2012 IEEE.

关键词： CCD cameras

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Interactive labeling of image segmentation hierarchies

Interactive labeling of image segmentation hierarchies

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Joint 34th Symposium of the German Association for pattern recognition, DAGM 2012 and 36th Symposium of the Austrian Association for pattern recognition, OAGM 2012

作者： Zankl, Georg Haxhimusa, Yll Ion, Adrian Pattern Recognition and Image Processing Group 186/3 Institute for Computer Aided Automation Vienna University of Technology Austria Institute of Science and Technology Austria

ISBN: (纸本)9783642327162

We study the task of interactive semantic labeling of a segmentation hierarchy. To this end we propose a framework interleaving two components: an automatic labeling step, based on a Conditional Random Field whose dependencies are defined by the inclusion tree of the segmentation hierarchy, and an interaction step that integrates incremental input from a human user. Evaluated on two distinct datasets, the proposed interactive approach efficiently integrates human interventions and illustrates the advantages of structured prediction in an interactive framework. © 2012 Springer-Verlag.

关键词： Semantics

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Accurate object tracking based on homography matrix

Accurate object tracking based on homography matrix

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2012 International Conference on Computer Science and Service System, CSSS 2012

作者： Zhang, Miaohui Hou, Yandong Hu, Zhentao Institute of Image Processing and Pattern Recognition Shanghai JiaoTong University Shanghai 200240 China School of Computer and Information Engineering Henan University Kaifeng 475004 China

ISBN: (纸本)9780769547190

We present a novel object tracking framework that can efficiently track such 2-D affine motions of the object image. A coarse-to-fine tracking strategy is explored in the tracking framework. Firstly, the object image region is selected from the first frame, the scale-invariant feature (SIFT) extracted from the object image region is utilized as the object model. Secondly, the highest likelihood object region is preliminarily located by the particle filter (PF) algorithm in the following video frame, and the SIFT feature points are also extracted from the highest likelihood object region, matching point set between object model and the highest likelihood region is attained by the scale-invariant feature transform, then the corresponding homography matrix is robustly estimated through the random sample consensus (RANSAC) algorithm. Finally, the affine parameters which determine the location and pose of the object are obtained. Simulation results demonstrate the efficiency of our approach. © 2012 IEEE.

关键词： Tracking (position)

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