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2010 International Conference on Computer Design and Applications, ICCDA 2010

作者： Zhou, Bing Yang, Xin-Xin Institute of Image Processing and Pattern Recognition Henan University Kai Feng China School of Computer and Information Engineering Henan University Kai Feng China

ISBN: (纸本)9781424471638

As we all know, the content-based image retrieval (CBIR) is very time-consuming due to the extraction and matching of high dimensional and complex features. The traditional CBIR systems could not respond to a very large number of retrieval requests at mean time, which are submitted from the Internet. In this paper, we propose a content-based parallel image retrieval system to achieve high responding ability. Our system is developed on cluster architectures. It has several retrieval servers to supply the service of content-based image retrieval. Our system adopts the Browser/Server (B/S) mode. The users could visit our system though web pages. Our system uses the Symmetrical Color-Spatial Features (SCSF)[25] to represent the content of an image. The SCSF is effective and efficient for image matching because it is independent of image distortion such as rotation and flip as well as it increases the matching accuracy. The SCSF was organized by M-tree(16), which could speedup the searching procedure. Our experiments show that the image matching is quickly and efficiently with the use of SCSF. And with the support of several retrieval servers, the system could respond to many users at mean time. © 2010 IEEE.

关键词： image matching

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Action recognition by multiple features and hyper-sphere multi-class SVM

Action recognition by multiple features and hyper-sphere mul...

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2010 20th International Conference on pattern recognition, ICPR 2010

作者： Liu, Jia Yang, Jie Zhang, Yi He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia

ISBN: (纸本)9780769541099

In this paper we propose a novel framework for action recognition based on multiple features for improve action recognition in videos. The fusion of multiple features is important for recognizing actions as often a single feature based representation is not enough to capture the imaging variations (view-point, illumination etc.) and attributes of individuals (size, age, gender etc.). Hence, we use two kinds of features: i) a quantized vocabulary of local spatio-temporal (ST) volumes (cuboids and 2-D SIFT), and ii) the higher-order statistical models of interest points, which aims to capture the global information of the actor. We construct video representation in terms of local space-time features and global features and integrate such representations with hyper-sphere multi-class SVM. Experiments on publicly available datasets show that our proposed approach is effective. An additional experiment shows that using both local and global features provides a richer representation of human action when compared to the use of a single feature type. © 2010 IEEE.

关键词： Spheres

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A novel method of aerial image classification based on attention-based local descriptors

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Procedia Earth and Planetary Science 2009年第1期1卷 1133-1139页

作者： Xu, Sheng Fang, Tao Huo, Hong Li, Deren Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China The State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan 430072 China

This paper proposes a novel method for object-based classification in very high spatial resolution aerial image. It combines the saliency maps very closely to extract the conspicuous local regions for better description of object and classification. Unlike the previous work on detection of the local regions, a biologically motivated selective attention model is presented in this paper, since not all the local regions are important for describing the objects. In order to model the attention region, we propose a new attention-based local descriptor using the saliency map and relative local features to reflect the region of interest (ROI). The experimental results on the VHR aerial image dataset show that the proposed approach can obtain the state-of-the-art classifica-tion performance. © 2009.

关键词： Object recognition image analysis image classification image segmentation Aerial images Bag of visual words Local descriptors Local feature Local region Novel methods Object based Region of interest Saliency map Selective attention model Very high spatial resolutions

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The influence of hubness on nearest-neighbor methods in object recognition

The influence of hubness on nearest-neighbor methods in obje...

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2011 IEEE 7th International Conference on Intelligent Computer Communication and processing, ICCP 2011

作者： Tomašev, Nenad Brehar, Raluca Mladenić, Dunja Nedevschi, Sergiu Artificial Intelligence Laboratory Jožef Stefan Institute Ljubljana Slovenia Image Processing and Pattern Recognition Group Technical University of Cluj-Napoca Romania

ISBN: (纸本)9781457714788

Object recognition from images is one of the essential problems in automatic image processing. In this paper we focus specifically on nearest neighbor methods, which are widely used in many practical applications, not necessarily related to image data. It has recently come to attention that high dimensional data also exhibit high hubness, which essentially means that some very influential data points appear and these points are referred to as hubs. Unsurprisingly, hubs play a very important role in the nearest neighbor classification. We examine the hubness of various image data sets, under several different feature representations. We also show that it is possible to exploit the observed hubness and improve the recognition accuracy. © 2011 IEEE.

关键词： Object recognition

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An implementation of postal numerals segmentation and recognition system for Chinese business letters 5

An implementation of postal numerals segmentation and recogn...

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5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Lu, Yue Shi, Pengfei Wu, Jianzhong Rui, Jianming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200030 China Third Research Institute Ministry of Post and Telecommunication Shanghai200062 China

ISBN: (纸本)0769503187

In this paper, a practical postal numeral segmentation and recognition system for Chinese business letters is presented. Line information for the address blocks is gained from the envelope image by projection, then the sub-image of the postal numerals is segmented. The numerals are recognized by three independent classifiers, and their results are combined to form final results. An improved voting principle based on a priori knowledge of each classifier is utilized to combine multiple classifiers in order to achieve perfect performance for high recognition rate and low error rate. The recognition ability of each classifier, acting with the voting principle, is obtained by statistics for a large set of samples. Different thresholds gained by training are employed for different classes, which can yield better results. A parallel structure hardware is designed to implement a real-time image processing system. The performance of the system is shown to be satisfactory, sufficient for the requirements of practical use. © 1999 IEEE.

关键词： Real time systems

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A self-calibration method for smart video cameras

A self-calibration method for smart video cameras

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2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

作者： Nebehay, Georg Pflugfelder, Roman Pattern Recognition and Image Processing Vienna University of Technology A-1040 Vienna Austria Video and Security Technology Austrian Institute of Technology A-1220 Vienna Austria

ISBN: (纸本)9781424444427

The automatic calibration of the intrinsic camera parameters such as the focal length and the camera orientation is an important pre-requisite for many computer vision algorithms in video surveillance. Despite its importance only a few number of methods show their applicability in embedded systems. This paper shows new results of previous work done in camera self-calibration on images of the York Urban data-set. These 102 images show typical urban scenes one might expect in practice. The evaluation shows that in 52 of 102 images the proposed method achieves less than 5% relative error in the focal length at a mean computation time per image of 14.45 s on a standard PC. We believe that these results show a fair balance between accuracy and computational performance and encourage an embedded implementation on a smart camera. ©2009 IEEE.

关键词： Video cameras

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Improved neural network based manifold learning method for face recognition with less face images per individual

Improved neural network based manifold learning method for f...

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2007 International Conference on image processing, Computer Vision, and pattern recognition, IPCV 2007

作者： Du, Chunhua Yang, Jie Wu, Zheng Yuan, Quan Wu, Qiang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Computer Systems University of Technology Sydney Sydney Australia

ISBN: (纸本)9781601320438

In this paper, a novel neural network based manifold learning method(NNBML)[1] recently appeared in the Journal of Science is introduced. It can effectively convert high-dimensional data into low-dimensional codes, which are then used for classification. However, it performs not well while dealing with small size face database used for face recognition. We propose a solution generating more samples data based on the existing data. The proposed method is implemented on two well-known face databases, viz. ORL and Yale face databases. The experimental results show that NNBML is able to deal with the task of face recognition after more data samples generated using the proposed method, and also that NNBML outperforms LDA in terms of recognition rate.

关键词： Neural networks

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An algorithm for radar scene matching based on multi-area selection using fuzzy sets

An algorithm for radar scene matching based on multi-area se...

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MIPPR 2005: image Analysis Techniques

作者： Yang, Weidong Zuo, Zhengrong Zhang, Tianxu Mao, Haicen State Key Laboratory of Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

Radar scene matching technique has been widely found in many application fields such as remote sensing, navigation, terrain-map match, scenery variance analysis and so on. Radar image geometry is quite different from that of optical satellite imagery, whose imaging is a slanting imaging of electromagnetic microwave reflection. The different characters between radar image and optical satellite images are very distinct, such as the layover distortion of ground-truth and speckle noise, which degrades the image to such an extent that the features are very unclear and difficult to be extracted. So the factors such as the hypsography, ground truth, sensor altitude and imaging time should be taken into account for radar image and optical image matching. In this paper, we develop an image match algorithm based on reference map multi-area selection using fuzzy sets. image matching is generally a procedure that calculates the similarity measurement between sensed image and the corresponding intercepted image in reference map and it searches the maximum position in the correlation map. Our method adopts a converse matching strategy which selects multi-areas in optical reference map using fuzzy sets as model images, then match them on the sensed image respectively by normalized cross correlation matching algorithm and fuse the match results to get the optimum registered position. Multi-areas selection mainly considers two influence factors such as ground-truth texture features and the hypsography (DEM) of imaging region, which will suppress the influence of great variance imaging region. Experiment results show the method is effective in registering performance and reducing the calculation.

关键词： Remote sensing

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Incremental-decremental algorithm for computing AT-models and persistent homology

Incremental-decremental algorithm for computing AT-models an...

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Lecture Notes in Computer Science

作者： Gonzalez-Diaz, Rocio Ion, Adrian Jimenez, Maria Jose Poyatos, Regina School of Computer Engineering University of Seville Spain Pattern Recognition and Image Processing Group Vienna University of Technology Austria Institute of Science and Technology Austria

ISBN: (纸本)9783642236716

In this paper, we establish a correspondence between the incremental algorithm for computing AT-models [8,9] and the one for computing persistent homology [6,14,15]. We also present a decremental algorithm for computing AT-models that allows to extend the persistence computation to a wider setting. Finally, we show how to combine incremental and decremental techniques for persistent homology computation. © 2011 Springer-Verlag.

关键词： Computers

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Profile-based Pottery Reconstruction

Profile-based Pottery Reconstruction

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Conference on Computer Vision and pattern recognition Workshop, CVPRW 2003

作者： Kampel, M. Sablatnig, R. Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology Favoritenstrasse 9 183-2 ViennaA-1040 Austria

ISBN: (纸本)0769519008

A major obstacle to the broader use of 3D object reconstruction and modeling is the extent of manual intervention needed. Such interventions are currently extensive and exist throughout every phase of a 3D reconstruction project: collection of images, image management, establishment of sensor position and image orientation, extracting the geometric information describing an object, and merging geometric, texture and semantic data. We present a fully automated approach to pottery reconstruction based on the fragment profile, which is the cross-section of the fragment in the direction of the rotational axis of symmetry. We demonstrate the method and give results on synthetic and real data. © 2003 IEEE.

关键词： Semantics

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