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6th international conference on Machine Vision, ICMV 2013

作者： Li, Qiaozhe Qiao, Yu Yang, Jie Bai, Li Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China School of Computer Science University of Nottingham Nottingham United Kingdom

ISBN: (纸本)9780819499967

In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. the joint sparse dictionary consists of positive and negative sub-dictionaries, which model foreground and background objects respectively. An online dictionary learning method is developed to update the joint sparse dictionary by selecting both positive and negative bases from bags of positive and negative image patches/templates during tracking. A linear classifier is trained with sparse coefficients of image patches in the current frame, which are calculated using the joint sparse dictionary. this classifier is then used to locate the target in the next frame. Experimental results show that our tracking method is robust against object variation, occlusion and illumination change. © 2013 SPIE.

关键词： E-learning

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Knife Detection Scheme Based on Possibilistic Shell Clustering

Knife Detection Scheme Based on Possibilistic Shell Clusteri...

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6th international conference on Multimedia Communications, Services and Security (MCSS)

作者： Maksimova, Aleksandra Natl Acad Sci Ukraine Inst Appl Math & Mech Donetsk Ukraine

ISBN: (纸本)9783642385599

this paper deals with a novel method for knife detection in images. the special feature of any knife is its simple geometric form. the proposed knife detection scheme is based on searching object with corresponding form. Fuzzy and possibilistic shell clustering methods are used to find contours of objects in the picture. these methods give as a result a set of second-degree curves offered in analytical form. To answer the question whether there is a knife in the picture, the angle between two such curves is calculated and its value is estimated. A C++ program was developed for experiments allowing to confirm the suitability of the proposed scheme for knife detection. Robustness of possibilistic c quadric shell clustering to outlier points let us use this algorithm in real-life situations. the objective of research is to use the results for developing a system for monitoring dangerous situation in urban environment using public CCTV systems.

关键词： fuzzy and possibilistic shell clustering pattern recognition knife detection geometric approach

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in bioinformatics) 2013年 7887 LNCS卷 V-VI页

作者： Sanches, João M. Micó, Luisa Cardoso, Jaime S. Instituto Superior Técnico Av. Rovisco Pais 1 1049-001 Lisboa Portugal University of Alicante Apartado de Correos 99 03080 Alicante Spain University of Porto Faculty of Engineering Campus Da FEUP Rua Dr. Roberto Frias no. 378 4200-465 Porto Portugal

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Energy-efficient threshold circuits detecting global pattern in 1-dimentional arrays

Energy-efficient threshold circuits detecting global pattern...

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10th international conference on theory and Applications of Models of Computation, TAMC 2013

作者： Suzuki, Akira Uchizawa, Kei Zhou, Xiao Graduate School of Information Sciences Tohoku University Aramaki-aza Aoba 6-6-05 Aoba-ku Sendai 980-8579 Japan Graduate School of Science and Engineering Yamagata University Johnan 4-3-16 Yonezawa-shi Yamagata 992-8510 Japan

ISBN: (纸本)9783642382352

In this paper, we investigate a relationship between energy and size of a threshold circuit processing a simple task, called PLRn, that was introduced in a context of pattern recognition. Formally, P LRn: {0, 1}n x {0, 1}n → {0,1} is defined as follows: For every x = (x1,x2,, xn) ∈ {0, 1}n and y = (y1,y 2,,yn) ∈ {0, 1}n, PLRn(x, y) = 1 if there exists a pair of indices i and j such that i i = yj = 1;and PLRn(x,y) = 0 otherwise. We prove that PLRn can be computed by a threshold circuit of energy e and size s = O (e · n 2/e-1) for any integer e, 3 ≤ e ≤ 2log2 n + 1. Our result implies that one can construct an energy-efficient circuit computing PLRn if it is allowable to use large size. Moreover, we focus on an extreme case where a threshold circuit has energy e = 1, and show that PLR can be computed by a threshold circuit of energy e = 1 and size s = ⌊n/2⌋, while PLRn cannot be computed by any threshold circuit of energy e = 1 and size s ≤ ⌊n/2⌋ - 1. © Springer-Verlag Berlin Heidelberg 2013.

关键词： pattern recognition

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Boosting deformable part model by sample sharing and outlier ablation

Boosting deformable part model by sample sharing and outlier...

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4th international conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Liu, Feng Huang, Yongzhen Wang, Liang Yang, Wankou School of Automation Southeast University Nanjing 210096 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642420566

the deformable part model (DPM) achieves the best performance on some well known datasets in terms of object detection. Literature springs up to study the success of such a model and hence various methods are proposed to improve it. Yet one import issue, the sensitivity to outliers of the hinge loss, has not been fully studied. In this paper, we take two initiatives to handle this problem: 1) we propose to share samples of one component to others by similarity;2) we give samples different weights according to their costs. the model is better trained with our proposed method, and we boost the performance of the newly released voc-release 5 [6] model on the challenging VOC 2007 dataset. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Object detection

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Crosspoint switching of EMG signals to increase number of channels for pattern recognition myoelectric control

Crosspoint switching of EMG signals to increase number of ch...

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international IEEE/EMBS conference on Neural Engineering, CNE

作者： Rudhram Gajendran Dennis C. Tkach Levi J. Hargrove University of lllinois at Chicago Rehabilitation Institute of Chicago Chicago IL Center for Bionic Medicine VHA Inc. Dallas TX Department of Physical Medicine and Rehabilitation at Northwestern University Rehabilitation Institute of Chicago Chicago IL USA

Myoelectric pattern recognition (PR) can provide a more intuitive control for upper limb amputees in using multifunction prosthesis than direct control. Accuracy of a pattern recognition system has been shown to improve with increasing number of EMG channels. However, increasing the number of channels comes with a drawback of increased weight, cost and complexity of the prosthesis. this paper presents the concept and design of a novel EMG acquisition system to acquire higher number of channels without increasing the number of electrodes placed or the complexity of the prosthetic device. A prototype of the device was developed and tested on able-bodied subjects to evaluate its performance in pattern recognition. Subjects were requested to perform 9 different hand movements while EMG data was collected into training and test groups. Test results indicate a 15% improvement in classification accuracy with the new system when compared to conventional systems. A system like this is valuable for patients with higher level amputations where placing higher number of electrodes is not feasible due to limited availability of appropriate muscle sites.

关键词： Electrodes Electromyography pattern recognition Muscles Prosthetics Switches

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Multi-layer perceptron training algorithms for pattern recognition of myoelectric signals

Multi-layer perceptron training algorithms for pattern recog...

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Biomedical Engineering international conference (BMEiCON)

作者： Le M.D. Khong Timothy J. Gale Danchi Jiang Jan C. Olivier Max Ortiz-Catalan School of Engineering University of Tasmania Hobart Australia University of Tasmania Hobart TAS AU Department of Signals and Systems Chalmers University of Technology Gothenburg Sweden

A challenge in using myoelectric signals in control of motorised prostheses is achieving effective signal pattern recognition and robust classification of intended motions. In this paper, the performance of Matlab's Multi-layer Perceptron (MLP) backpropogation training algorithms in motion classification were assessed. the test and evaluation platform used was “BioPatRec”, a Matlab-based open-source prosthetic control development environment, together with algorithms sourced from Matlab's neural network toolbox. the algorithms were used to interpret multielectrode myoelectric signals for motion classification, with the aim of finding the best performing algorithm and network model. the results showed that Matlab's trainlm and trainrp algorithms could achieve a higher accuracy than other tested MLP training algorithms (94.13 ± 0.037% and 91.09 ± 0.047%, respectively). Discussion of these results investigates significant features to obtain the highest performance.

关键词： Training Accuracy Classification algorithms pattern recognition Backpropagation MATLAB Feature extraction

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A Real Time Performance Assessment of Simultaneous pattern recognition Control for Multi-functional Upper Limb Prostheses

A Real Time Performance Assessment of Simultaneous Pattern R...

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international IEEE/EMBS conference on Neural Engineering

作者： Sophie M. Wurth Levi J. Hargrove Swiss Federal Institute of Technology in Lausanne Department of Physical Medicine and Rehabilitation Northwestern University

ISBN: (纸本)9781467319676

A natural and intuitive operation of multifunctional upper limb prostheses involves the concurrent activation of multiple degrees of freedom in a proportional way. Several approaches to simultaneous and proportional control strategies have been investigated;provided outcome measures however were offline accuracy or error rates and lacked the functional component of a preclinical assessment. this study evaluated a simultaneous proportional pattern recognition control strategy with two parallel classifiers in a two-dimensional Fitts' law style test and compared it to a sequential pattern recognition approach. the proposed test allowed for a complete evaluation through different performance metrics such as throughput (TP, bits/sec), path efficiency (PE,%), completion rate (%), overshoot (%) and reaction time (sec). We found that the simultaneous approach presented with numerous advantages with respect to the sequential alternative through significantly higher TP and PE for combined-motion targets (p<0.001) and significantly less overshooting in both combined and discrete targets (p<0.01). For discrete motions, the TP was significantly lower for the simultaneous approach (p<0.001) but PE was similar. there was no difference in either completion rate or reaction time. these results support the potential of simultaneous pattern recognition for the control of multifunctional prostheses and underline the usefulness of a simple functional test in a preclinical framework.

关键词： Artificial Limbs pattern recognition Degree of freedom Polyethylenes Performance metrics Prosthesis Concurrency functional testing Upper Extremity Reaction Time Error analysis overshooting Performance assessment control strategy SEQUENTIAL pattern recognition

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Sequential record based compression for massive image storage in database

Sequential record based compression for massive image storag...

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14th international conference on Web-Age Information Management, WAIM 2013

作者： Ma, Ziyun Wang, Xiaonian Jiang, Ping Jin, Jiajun Guo, Silu Department of Information and Control Tongji University Shanghai 200092 China Department of Computer Science University of Hull HU6 7RX United Kingdom

ISBN: (纸本)9783642395260

With the development of automatic management for industrial manufactory, the applications involving computer-vision and pattern recognition are widely used. the advantages of these modern methods using database to store a large sequence of images for helping management have been widely recognized. However, the storage of massive images into a database may demand a large memory space and cause a slow access speed. To increase the utilization rate of storage space and improve the performance of the database, this paper proposes an image compression scheme which is learnt from video compression to remove temporal and spatial redundancy in the image sequence. the proposed scheme not only alleviates the above issues associated with image storage but also keeps the basic database operations valid to image access, such as, insert, delete and update. At the end of this paper, we use the result to solve the optimizing storage problem successfully for a packaging machine which is computer-vision based quality monitoring. © 2013 Springer-Verlag.

关键词： Database systems

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Towards Improved Partial-Hand Prostheses: the Effect of Wrist Kinematics on pattern-recognition-Based Control

Towards Improved Partial-Hand Prostheses: The Effect of Wris...

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international IEEE/EMBS conference on Neural Engineering

作者： Adenike A. Adewuyi Levi J. Hargrove Todd A. Kuiken Department of Biomedical Engineering at Northwestern University Department of Physical Medicine and Rehabilitation at Northwestern University Departments of Physical Medicine and Rehabilitation Biomedical Engineering and Surgery at Northwestern University

ISBN: (纸本)9781467319676

pattern-recognition-based control using surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for providing control of multiple prosthetic functions. However, it is not clear how these systems will perform when the user possesses a functional wrist;an attribute unique to the population of partial-hand amputees. Fortunately, partial-hand amputees may have remaining intrinsic hand muscles, from which additional information-rich EMG data may be extracted and used for prosthetic control. We investigated the effect of statically and dynamically varying wrist position on a pattern recognition system's ability to classify hand grasp patterns in able-bodied individuals. We found that varying wrist position significantly degraded the system's performance (p<0.001). the system performed worse when trained only with EMG data from the extrinsic hand muscles than when trained with EMG data from the intrinsic hand muscles. the system's performance significantly improved when trained in all static wrist positions (p<0.001) and with all dynamic wrist motions (p<0.001).

关键词： Wrist Muscles Electromyography Dynamics Electrodes Prosthetics pattern recognition

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