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Investigating visual feature extraction methods for image annotation

Investigating visual feature extraction methods for image an...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Rukun Hu Shuai Shao Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

In order to investigate the performance of visual feature extraction method for automatic image annotation, three visual feature extraction methods, namely discrete cosine transform, Gabor transform and discrete wavelet transform, are studied in this paper. These three methods are used to extract low-level visual feature vectors from images in a given database separately, then these feature vectors are mapped to high-level semantic words to annotate images with labels in a given semantic label set. As it is more efficient to depict the visual features of an image by the feature distribution than to resort to image segmentation technology for semantic image blocks, this paper is going to find out which of the three feature extraction methods performs better in image annotation based on the distribution of feature vectors from the image. The performance of three different kinds of feature extraction method is fully analyzed, and it is found that discrete cosine transform method is more suitable for Gaussian mixture model in automatic image annotation.

关键词： Feature extraction Discrete wavelet transforms Discrete cosine transforms Shape image databases Spatial databases Visual databases image analysis Performance analysis Bayesian methods

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A non-continuous wavelength scanning strategy for electrically tunable liquid-crystal hyperspectral imaging array

A non-continuous wavelength scanning strategy for electrical...

引用

MIPPR 2009 - Multispectral image Acquisition and processing: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Liu, Kan Li, Dehua Zhang, Xinyu Li, Hui Wu, Li Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multispectral Information Processing Technology Huazhong University of Science and Technology Wuhan 430074 Hubei China College of Technology and Engineering Yangtze University Jingzhou 434020 Hubei China

ISBN: (纸本)9780819478054

Traditional mechanically tunable imaging spectrometry, including those based on MEMS technology, can only obtain continuous spectral image data in a fixed spectral order, which was restricted by the moving mechanism of the mechanical device. But spectrum absorption peakof materials is not continuous, especially in hyperspectral scale. To overcome such shortages, a smart spectral imaging detection method based on the integration of electrically tunable liquid-crystal (LC) Fabry-Perot (FP) microstructure array and a non-continuous wavelength choosing strategy to operation the device are proposed. With a tunable LC-FP array composed by many working units arranging in two dimensions, the device can image in hundreds of spectral bands simultaneity within milliseconds in a calibrated system, and making correct detection for certain objects in one shot. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Absorption spectroscopy

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Spatio-temporal fusion for reliable moving vehicle classification in wireless sensor networks

Spatio-temporal fusion for reliable moving vehicle classific...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Chunting Liu Hong Huo Tao Fang Deren Li Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China LIESMARS Wuhan University of China Wuhan China

One of the important tasks in sensor networks is classifying moving vehicles. Fusion of large amount of sensor measurements can improve network performance and reduce the consumption of sensor network resource. We study using continuous measurements of multiple sensor nodes to improve the classification performance by spatio-temporal fusion and fault detection. Time series decisions of single sensor node are aggregated to make a reliable classification estimation. A fusion center combines local classification decisions and evaluates the correctness of these decisions. A correctness status is sent back to each sensor node. Based on the status, sensor nodes can adjust their temporal fusion result. Simulation results demonstrate the validity of our method.

关键词： Vehicles Wireless sensor networks Sensor fusion Fault detection Sensor phenomena and characterization Signal processing algorithms Collaboration Computational modeling Interference Cybernetics

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Refining Content Based image Retrieval via Semi-Supervised Learning

Refining Content Based Image Retrieval via Semi-Supervised L...

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European signal processing conference

作者： Songhao Zhu Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University 800 Dong Oman Road 200240 Shanghai China

ISBN: (纸本)9781617388767

Content-based image retrieval plays a key role in the management of a large image database. However, the results of existing approaches are not as satisfactory for the gap between visual features and semantic concepts. Therefore, a novel scheme is here proposed. First, to tackle the problem of large computational cost involved in a large image database, a pre-filtering processing is utilized to filter out the most irrelevant images while keeping the most relevant ones. Second, the relevance between the query image and the remaining images is measured and the obtained relevance scores are stored for a later refinement processing. Finally, a semi-supervised learning algorithm is utilized to refine candidate ranking by taking into account both thepairwise information of unlabeled images and the relevance scores between the input query image and unlabeled images. Experiments conducted on a typical Corel dataset demonstrate the effectiveness of the proposed scheme.

关键词： Semi-supervised Learning content-based image retrieval visual databases image retrieval Refining Purification

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Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets

Invariant Primitives for Handwritten Arabic Script: A Contra...

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International Conference on Document Analysis and recognition

作者： Sofiene Haboubi Samia Maddouri Noureddine Ellouze Hailkal El-Abed Image Processing and Pattern Recognition Unit National Engineering School of Tunis (ENIT) Tunis Tunisia Department of Signal Processing of Mobile Information Systems Institute for Communications Technology Brunswick Germany

ISBN: (纸本)9781424445004

The choice of relevant features is very decisive in handwriting recognition rate. Our aim is to present some useful structural and statistical features and see their degree of variability. In this paper, we start with a description of the variability of the Arabic handwriting and the way how to reduce it. Four kinds of feature sets used by our handwriting systems are then presented evaluated and discussed. The comparison is carried on a database of images from IFN/ENIT databases. The neural network multilayer perceptrons is our method of classification. A contrastive study of these primitives is done according to recognition their time and memory consuming and their variability degree.

关键词： Handwriting recognition image segmentation image analysis pattern recognition image recognition image databases Spatial databases Skeleton Data mining Text analysis

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Incremental learning in nonstationary environments with controlled forgetting

Incremental learning in nonstationary environments with cont...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ryan Elwell Robi Polikar Signal Processing and Pattern Recognition Laboratory Electrical and Computer Engineering Department Rowan University Glassboro NJ USA

We have recently introduced an incremental learning algorithm, called Learn ++ .NSE, designed for Non-Stationary Environments (concept drift), where the underlying data distribution changes over time. With each dataset drawn from a new environment, Learn ++ .NSE generates a new classifier to form an ensemble of classifiers. The ensemble members are combined through a dynamically weighted majority voting, where voting weights are determined based on classifiers' age-adjusted accuracy on current and past environments. Unlike other ensemble-based concept drift algorithms, Learn ++ .NSE does not discard prior classifiers, allowing potentially cyclical environments to be learned more effectively. While Learn ++ .NSE has been shown to work well on a variety of concept drift problems, a potential shortcoming of this approach is the cumulative nature of the ensemble size. In this contribution, we expand our analysis of the algorithm to include various ensemble pruning methods to introduce controlled forgetting. Error or age-based pruning methods have been integrated into the algorithm to prevent potential out-voting from irrelevant classifiers or simply to save memory over an extended period of time. Here, we analyze the tradeoff between these precautions and the desire to handle recurring contexts (cyclical data). Comparisons are made using several scenarios that introduce various types of drift.

关键词： Neutron spin echo Algorithm design and analysis Voting

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A new tracking method for small infrared targets

A new tracking method for small infrared targets

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IEEE International Conference on image processing

作者： Lei Yang Weiping Lu Jie Yang Physics Department EPS Heriot-Watt University Edinburgh UK Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

We report on a new approach to tracking small infrared targets. The method improves on existing target trackers by combining mean-shift tracker with Kalman filtering and by updating the tracking parameters through the measurement of the complexity of the target region. We have further developed a nonlinear algorithm to improve the robustness of the traditional mean-shift tracker for small infrared targets. Experimental results demonstrate a superior performance of our method compared to existing target trackers, particularly in the environment of strong measurement noise and large variation of illumination.

关键词： Target tracking Noise robustness Noise measurement Lighting Video sequences Kalman filters Filtering Particle measurements Working environment noise Robust stability

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3D Face Pose Normalization Using Equipartition Fitting Sphere Representation of Shape

3D Face Pose Normalization Using Equipartition Fitting Spher...

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International Conference on image and Graphics (ICIG)

作者： Peijiang Liu Yunhong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9780769552378;9780769538839

Pose normalization is a necessary process of 3D face recognition. Automatic and robust normalization is still a challenge to existing techniques. We propose a novel method called Equipartition Fitting Sphere Representation (EPFSR) for shape representation. Convexes on face are localized firstly based on EPFSR. Then the tip and orientation of nose are identified automatically from convexes by template matching. Extensive experiments are performed on five popular 3D face databases. Results show the high robustness of the proposed methods to expression variations. Accuracy of nose identification is more than 97.7%. Time cost depends on the number of face vertices. It takes averagely less than 9 seconds to localize the nose on a 3D head including around 80000 vertices in the FRGC2.0 database.

关键词： Shape Nose Face recognition Clouds Robustness Databases Costs Face detection Humans Computer graphics

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Use Fukunaga-Koontz Transform to Solve Occlusion Problems in Multitarget Tracking

Use Fukunaga-Koontz Transform to Solve Occlusion Problems in...

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Chinese Conference on pattern recognition (CCPR)

作者： Yan Zhang Fanglin Wang Shengyang Yu Third Research Institute of Ministry of Public Security Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

For multitarget tracking problems, occlusions between targets are quite tough tasks. We present a novel algorithm to solve such problems. For the two targets in occlusions, Fukunaga-Koontz transform is exploited to achieve the projection matrix, with which the two targets are projected into a low dimensional space where they are quite distinguishing. To solve the problem of the change of target appearance, the eigenspace model is used as the probabilistic observation model, with which the algorithm can learn the changes of the target appearance online. These two procedures are evaluated in the particle filter based tracking framework. Experimental results demonstrated the effectiveness of our algorithm.

关键词： Target tracking Yttrium Particle filters Particle tracking Application software Equations Security image processing pattern recognition Computer vision

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Predicting Soft Tissue Deformation Based on an Improved Biomechanical Model

Predicting Soft Tissue Deformation Based on an Improved Biom...

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International Conference on Information Technology and Computer Science, ITCS

作者： Shengzheng Wang Jie Yang Chaojian Shi Merchant Marine College Shanghai Maritime University Shanghai China Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper presents an improved biomechanical model for the prediction of the soft tissues in the plastic surgical simulator. The new model is built on nonlinear finite mixed-element method (NFM-EM) in which the internal soft tissues (muscles and fat) are discretized into tetrahedral solid elements and the skin tissues into triangular shell elements, which distinguishes between the internal soft tissues and the skin in their geometrical structures, and addresses the non-homogenous problem of the facial soft tissues in their biomechanical characteristics. Moreover, after the investigation of the three different nonlinear strain-potential models, the biomechanical characteristics of the skin and the internal soft tissues are modeled with the most suitable one. The quantitative validation and the comparative results with other models illustrated the effectiveness of the approach on the simulation of complex cranio-facial surgery.

关键词： Biological tissues Deformable models Predictive models Skin Muscles Surgery Solid modeling Plastics Content addressable storage Biological materials

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