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检索条件"任意字段=MIPPR 2007: Pattern Recognition and Computer Vision"

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Efficient Image Processing with the Apply Language

Efficient Image Processing with the Apply Language

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Leonard G. C. Hamey Macquarie University Sydney Australia

ISBN: (纸本)9781424431618

Apply is a Domain-Specific Language for image processing and low-level computer vision. Apply allows programmers to write kernel operations that focus on the computation for a single pixel location. The compiler generates code to perform the kernel computation over entire images. The original Apply implementation was developed 20 years ago for efficient processing on parallel architectures. The current-generation Apply compiler targets efficient code generation for general-purpose computers, typically outperforming handwritten code, while maintaining the simplicity of the original language. The use of modern compiler writing tools, specifically Stratego/XT, has facilitated improvements in the language design and made it easy to target the compiler to different environments. A large number of computer vision and image processing operations can be expressed in Apply. However, some algorithms require additional features. To motivate future language development, we analyse the requirements of the algorithms provided in a commercial machine vision library.

关键词： Image processing computer vision Kernel Domain specific languages Programming profession Parallel architectures Writing Algorithm design and analysis Machine vision Libraries

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Ruttier Obstacle Classification by use of Fractional B-spline Wavelets and Moments

Ruttier Obstacle Classification by use of Fractional B-splin...

引用

Eurocon

作者： Anca Discant Simina Emerich Eugen Lupu Alexandrina Rogozan Abdelaziz Bensrhair Basis of Electronics Department Technical University of Cluj Napoca Cluj-Napoca Romania Communications Department Technical University of Cluj Napoca Cluj-Napoca Romania Department of Computer Science and Information Engineering National Institute for Applied Sciences Rouen France

Applications of wavelet analysis are widespread and cover many fields of scientific research including image processing, classification and recognition. In addition, the mathematical concept of moments has been used for many years in pattern recognition and image processing. We present a new discovered family of splines, named fractional B-splines which we used as mother wavelet functions. The resulted fractional B-spline wavelets constitute a part of the features vector used in our ruttier obstacle classification system. We compared different recognition rates obtained by the use of different mother wavelet functions, but in order to improve the recognition rates, we added first order statistics features and the seven moments of Hu. The artificial vision systems was developed having as model the human system, and therefore the objects recognition task is reduced to a classification using features extracted from images. In our case, the features vector is formed by wavelet transform of fractional B-splines and seven statistics features, followed by the seven moments of Hu.

关键词： Spline Image recognition Image processing Statistics Wavelet analysis Image analysis pattern recognition Machine vision Humans Object recognition

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Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning

Towards weakly supervised semantic segmentation by means of ...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Alexander Vezhnevets Joachim M. Buhmann ETH Zurich Zurich Switzerland

We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of only image level labels during training - the information whether a certain object is present or not in the image. Such coarse tagging of images is faster and easier to obtain as opposed to the tedious task of pixelwise labeling required in state of the art systems. We cast this task naturally as a multiple instance learning (MIL) problem. We use Semantic Texton Forest (STF) as the basic framework and extend it for the MIL setting. We make use of multitask learning (MTL) to regularize our solution. Here, an external task of geometric context estimation is used to improve on the task of semantic segmentation. We report experimental results on the MSRC21 and the very challenging VOC2007 datasets. On MSRC21 dataset we are able, by using 276 weakly labeled images, to achieve the performance of a supervised STF trained on pixelwise labeled training set of 56 images, which is a significant reduction in supervision needed.

关键词： Pixel Image segmentation Labeling Tagging Bellows Testing Object segmentation Face detection computer vision Humans

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An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams

An Incremental On-line Parsing Algorithm for Recognizing Ske...

引用

International Conference on Document Analysis and recognition

作者： J. Mas G. Sanchez J. Llados B. Lamiroy Computer Vision Center Department Ciències de la Computació Edifici O Universidad Autonoma de Barcelona Bellaterra Spain Ecole des Mines INPL and LORIA Nancy France

This paper presents a syntactic recognition approach for on-line drawn graphical symbols. The proposed method consists in an incremental on-line predictive parser based on symbol descriptions by an adjacency grammar. The parser analyzes input strokes as they are drawn by the user and is able to get ahead which symbols are likely to be recognized when a partial subshape is drawn in an intermediate state. In addition, the parser takes into account two issues. First, symbol strokes are drawn in any order by the user and second, since it is an on-line framework, the system requires real-time response. The method has been applied to an on-line sketching interface for architectural symbols.

关键词： Shape Text analysis Image recognition Graphics pattern recognition computer vision Real time systems Human computer interaction Heart Image analysis

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An Online HDP-HMM for Joint Action Segmentation and Classification in Motion Capture Data

An Online HDP-HMM for Joint Action Segmentation and Classifi...

引用

IEEE computer Society Conference on computer vision and pattern recognition Workshops

作者： Ava Bargi Richard Yi Da Xu Massimo Piccardi Faculty of Engineering and IT University of Technology Sydney PO Box 123 Broadway NSW 2007 Australia

ISBN: (纸本)9781467316118

Since its inception, action recognition research has mainly focused on recognizing actions from closed, predefined sets of classes. Conversely, the problem of recognizing actions from open, possibly incremental sets of classes is still largely unexplored. In this paper, we propose a novel online method based on the “sticky” hierarchical Dirichlet process and the hidden Markov model [11, 5]. This approach, labelled as the online HDP-HMM, provides joint segmentation and classification of actions while a) processing the data in an online, recursive manner, b) discovering new classes as they occur, and c) adjusting its parameters over the streaming data. In a set of experiments, we have applied the online HDP-HMM to recognize actions from motion capture data from the TUM kitchen dataset, a challenging dataset of manipulation actions in a kitchen [12]. The results show significant accuracy in action classification, time segmentation and determination of the number of action classes.

关键词： Online HDP-HMM Joint Action Data capture Action motion capture segmentation Segmentation Hidden Markov models KITCHEN

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A Two Stage recognition Scheme for Handwritten Tamil Characters

A Two Stage Recognition Scheme for Handwritten Tamil Charact...

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International Conference on Document Analysis and recognition

作者： U. Bhattacharya S.K. Ghosh S. Parui Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

India is a multilingual multiscript country with more than 18 languages and 10 different major scripts. Not enough research work towards recognition of handwritten characters of these Indian scripts has been done. Tamil, an official as well as popular script of the southern part of India, Singapore, Malaysia, and Sri Lanka has a large character set which includes many compound characters. Only a few works towards handwriting recognition of this large character set has been reported in the literature. Recently, HP Labs India developed a database of handwritten Tamil characters. In the present paper, we describe an off-line recognition approach based on this database. The proposed method consists of two stages. In the first stage, we apply an unsupervised clustering method to create a smaller number of groups of handwritten Tamil character classes. In the second stage, we consider a supervised classification technique in each of these smaller groups for final recognition. The features considered in the two stages are different. The proposed two-stage recognition scheme provided acceptable classification accuracies on both the training and test sets of the present database.

关键词： Character recognition Handwriting recognition Spatial databases pattern recognition Testing Speech recognition computer vision Natural languages Clustering methods Personal communication networks

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Preliminary level cardiac abnormality detection using wireless telecardiology system 1

Preliminary level cardiac abnormality detection using wirele...

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1st International Conference on the Digital Society, ICDS 2007

作者： Mitra, M. Mitra, S. Bera, J.N. Gupta, R. Chaudhuri, B.B. Dept. of Applied Physics University of Calcutta India Computer Vision and Pattern Recognition Unit ISI Kolkata India

ISBN: (纸本)0769527604

This paper describes a portable diagnostic telecardiology system, aimed to benefit the rural people of a third world country like India. The designed system consists of two major blocks;the first one is required to be carried to the patient home, named ¿Portable Telecardiology Kit¿. The second one, named ¿Automated Cardiac Signal Processor¿, a PC based system, to be permanently placed at the nearest rural health care center. The ¿Portable Telecardiology Kit¿ contains a portable ECG machine, a dedicated microcontroller-based full duplex communication system, both interfaced, in a single enclosure. This kit will convert the ECG signal along with a tag page (containing different information regarding patient¿s health and history of illness) to a digitized serial electromagnetic wave. The signal may be transmitted over a distance of about 7-10 km through a cordless phone under full duplex mode. The PC-based system, after receiving the transmitted signal from patient site, extract the ECG signal after proper filtering, and then pass the signal through an in-built knowledge-base. Finally, a rule-based rough set decision system is generated for the development of an inference engine for disease identification from these time-plane features. The system will generate a report indicating the preliminary level abnormalities, and the precautions that can be adopted at an early stage. The entire report is then sent to the Portable kit at the patient bed-site. © 2007 IEEE.

关键词： Electrocardiograms

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A method for multiple morph targets tracking based on region growing

A method for multiple morph targets tracking based on region...

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International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Heng-Xin Chen Bin Fang Yuan-Yan Tang College of Computer Science Chongqing University Chongqing China

It is very important to count passengers who get on and get off for scheduling bus effectively. The tracking methods based on target shape and feature points can not be adopted to this case, because the target shapes keep changing from time to time randomly and even appear partially in field of vision captured. Based on difference image and region growing, a new method is proposed in this paper for tracking the multiple moving targets whose shapes are variable. The result of experiment shows that the method is able to count passengers with preferable accuracy in real-time application.

关键词： Target tracking Shape Cameras Wavelet analysis pattern analysis pattern recognition Object detection Streaming media Color

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Expanding the usage of the star sensor in spacecraft

Expanding the usage of the star sensor in spacecraft

引用

2nd International Conference on Space Information Technology

作者： Zhang Hua Sang Hongshi Shen Xubang Huazhong Univ Sci & Technol Inst Pattern Recognit & AI Wuhan 430074 Peoples R China Xian Microelect Technol Inst Xian 710054 Peoples R China

ISBN: (纸本)9780819469601

Star sensors and computer vision systems are generally used for spacecraft navigation in deep space, both of which make use of image sensors. To mitigate the payload of the spacecraft, a new star sensor prototype with extending use as a rendezvous and docking positioning system is described in this paper. An adaptive processing element is used to control the process of image acquiring, image pre-processing and image recognition, which makes the sharing of the image sensor feasible. The software is discussed about how to realize the two applications. The earth based experiments verify the feasibility and validity of the design, which may make a little contribution on the deep space explorations.

关键词： deep space exploration navigation attitude determination rendezvous and docking star sensor image processing

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Off-Line Handwritten Character recognition of Devnagari Script

Off-Line Handwritten Character Recognition of Devnagari Scri...

引用

International Conference on Document Analysis and recognition

作者： U. Pal N. Sharma T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Japan

In this paper we present a system towards the recognition of off-line handwritten characters of Devnagari, the most popular script in India. The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2times2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. The normalized image is then segmented to 49times49 blocks and a Roberts filter is applied to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the blocks and the directions are down sampled using Gaussian filter to get 392 dimensional feature vector. A modified quadratic classifier is applied on these features for recognition. We used 36172 handwritten data for testing our system and obtained 94.24% accuracy using 5-fold cross-validation scheme.

关键词： Character recognition Handwriting recognition Filters Filtering pattern recognition Image segmentation Automation computer vision System testing Natural languages

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