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Gait recognition Using Local Ternary pattern (LTP)

Gait Recognition Using Local Ternary Pattern (LTP)

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3rd IEEE international conference on Signal and Image Processing Applications (ICSIPA)

作者： Low, K. B. Sheikh, U. U. Univ Teknol Malaysia Fac Elect Engn Dept Elect & Comp Engn Comp Vis Video & Image Proc CvviP Lab Skudai Malaysia

ISBN: (纸本)9781479902699;9781479902675

Local Ternary pattern (LTP) is usually applied for texture classification problems. In this work, we propose LTP for human gait characterization for the purpose of human identification. Our proposed method is based on the Gait Energy Image (GEI) whereby edge information over a complete gait cycle is extracted. However, GEI does not contain enough human body structure information for human recognition purpose. Therefore, LTP is used to extract texture information from all pixels in the human gait region which preserves more discriminative features of the subject. Gait cycle estimation is computed by using the aspect ratio of the subject's bounding box. After that, LTP features are averaged over a full gait cycle and a 2D joint histogram of the LTP is computed. At the end, K nearest-neighbor (k-NN) is used to obtain the final recognition results. The proposed method achieved higher accuracy compared to other methods when tested on the CMU MoBo human gait database. The proposed LTP method is easy to implement and also has the advantage of significantly lower computation time.

关键词： edge detection gait analysis image classification image texture

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Motion dense sampling for video classification

Motion dense sampling for video classification

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3rd international conference on IT Convergence and Security (ICITCS)

作者： Aihara, Kazuaki Aoki, Terumasa Tohoku Univ Grad Sch Informat Sci Sendai Miyagi 980 Japan Tohoku Univ Grad Sch Informat Sci New Ind Creat Hatchery Ctr Sendai Miyagi 980 Japan

ISBN: (纸本)9781479928453

In this paper, we propose the motion dense sampling (MDS) for video classification, which detects very informative interest points from video frames. MDS has two advantages compared to other existing methods. The first advantage is that MDS detects only interest points which belong to foreground regions of all regions of a video frame. Also it can detect the constant number of points even when the size of foreground region in an image drastically changes. The Second one is that MDS enable to describe scale invariable features by computing sampling scale for each frame based on the size of foreground regions. Thus, our method detects much more informative interest points from videos than other methods. Experimental results show a significant improvement over existing methods on YouTube dataset. Our method achieves 86.8% accuracy for video classification by using only one descriptor.

关键词： Accuracy Computer vision conferences Feature extraction Optical imaging pattern recognition YouTube

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Autonomous Learning of Domain Models using Two-Dimensional Probability Distributions

Autonomous Learning of Domain Models using Two-Dimensional P...

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IEEE 3rd Joint international conference on Development and Learning and Epigenetic Robotics (ICDL)

作者： Sowiski, Witold Guerin, Frank Univ Aberdeen Aberdeen AB9 1FX Scotland

ISBN: (纸本)9781479910366

An autonomous agent placed without any prior knowledge in an environment without goals or a reward function will need to develop a model of that environment using an unguided approach by discovering patters occurring in its observations. We expand on a prior algorithm which allows an agent to achieve that by learning clusters in probability distributions of one-dimensional sensory variables and propose a novel quadtree-based algorithm for two dimensions. We then evaluate it in a dynamic continuous domain involving a ball being thrown onto uneven terrain, simulated using a physics engine. Finally, we put forward criteria which can be used to evaluate a domain model without requiring goals and apply them to our work. We show that adding two-dimensional rules to the algorithm improves the model and that such models can be transferred to similar but previously-unseen environments.

关键词： continuous systems learning systems pattern recognition quadtrees robots statistical distributions

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Motion trend patterns for action modelling and recognition

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15th international conference on Computer Analysis of Images and patterns, CAIP 2013

作者： Nguyen, Thanh Phuong Manzanera, Antoine Garrigues, Matthieu ENSTA-ParisTech 828 Boulevard des Maréchaux 91762 Palaiseau Cedex France

ISBN: (纸本)9783642402609

A new method for action modelling is proposed, which combines the trajectory beam obtained by semi-dense point tracking and a local binary trend description inspired from the Local Binary patterns (LBP). The semi dense trajectory approach represents a good trade-off between reliability and density of the motion field, whereas the LBP component allows to capture relevant elementary motion elements along each trajectory, which are encoded into mixed descriptors called Motion Trend patterns (MTP). The combination of those two fast operators allows a real-time, on line computation of the action descriptors, composed of space-time blockwise histograms of MTP values, which are classified using a fast SVM classifier. An encoding scheme is proposed and compared with the state-of-the-art through an evaluation performed on two academic action video datasets. © 2013 Springer-Verlag.

关键词： Local binary pattern

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Research of characteristics extraction based on dynamic pressure signal

Research of characteristics extraction based on dynamic pres...

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3rd international conference on Intelligent Structure and Vibration Control, ISVC 2013

作者： Liu, Wei Liu, Hong Zhao School of Mechanical and Precision Instrument Engineering Xi'an University of Technology Xi'an 710048 China Computer Science and Technology Department Shaanxi Xueqian Normal University Xi'an 710061 China

ISBN: (纸本)9783037857236

The accuracy of pattern recognition was determined by the feature selection, and two methods of the characteristic description were discussed. The results show that the statistical characteristics could be used as a dynamic pressure signal descriptor, and the oscillation characteristic of curve is not suitable for describing dynamic pressure signal by itself. The selection of descriptors of dynamic pressure signal is the precondition to identify the leak signal and the non-leak signal effectively. © (2013) Trans Tech Publications, Switzerland.

关键词： pattern recognition

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Using LS-SVM pattern recognizer to detect change-point in ARMA process

Using LS-SVM pattern recognizer to detect change-point in AR...

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3rd international conference on Frontiers of Manufacturing and Design Science (ICFMD 2012)

作者： Cheng Zhiqiang North China Univ Water Resources & Elect Power Sch Management & Econ Zhengzhou 450011 Henan Peoples R China

ISBN: (纸本)9783037855782

Based on LS-SVM pattern recognizer, this paper develops an intelligent method for solving the problem of change-point detection, and the proposed model is applied to detect change-point of process mean-shift in auto-correlated time series process. In this research, LS-SVM algorithm and moving window method are used to detect the location of the mean shift signal, the LS-SVM pattern recognizer is designed and the performance of the recognizer is evaluated in terms of Accuracy Rate. Results of simulation experiment show that the proposed intelligent model is an effective method to detect change-point in ARMA data series.

关键词： change-points detection least squares support vector machine pattern recognition ARMA process

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Image Analysis - 18th Scandinavian conference, SCIA 2013, Proceedings

Image Analysis - 18th Scandinavian Conference, SCIA 2013, Pr...

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18th Scandinavian conference on Image Analysis, SCIA 2013

ISBN: (纸本)9783642388859

The proceedings contain 67 papers. The topics discussed include: texture description with completed local quantized patterns;a local image descriptor robust to illumination changes;detection of curvilinear structures by tensor voting applied to fiber characterization;simple-graphs fusion in image mosaic: application to automated cell files identification in wood slices;unsupervised segmentation of anomalies in sequential data, images and volumetric data using multiscale Fourier phase-only analysis;extended 3D Line Segments from RGB-d data for pose estimation;incorporating texture intensity information into LBP-based operators;Bayesian non-parametric image segmentation with Markov random field prior;evaluating local feature detectors in salient region detection;forest stand delineation using a hybrid segmentation approach based on airborne laser scanning data;and mean shift with flatness constraints.

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Influence of exceptional data on bridge damage assessment based on one-class SVM pattern recognition

Influence of exceptional data on bridge damage assessment ba...

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3rd international conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2013

作者： Furuta, H. Nomura, Y. Nakatsu, K. Hattori, H. Yasuda, S. Faculty of Informatics Kansai University Japan Department of Science and Engineering Ritsumeikan University Japan Department of Modern Life Osaka Jonan Women's Junior College Japan Graduate School of Engineering Kyoto University Japan Graduate School of Informatics Kansai University Japan

ISBN: (纸本)9781905088584

Recently, it has become difficult to ensure the skill level of bridge maintenance engineers as a result of the retirement of experienced engineers. Hence, the daily inspection of bridges cannot be performed accurately and efficiently for the early detection of damage and to ensure appropriate measures. In previous research, damage assessment by introducing the technology of pattern recognition of digital images has been proposed. However, in the previous research, it was confirmed that there were some images which might be considered as exceptional data among the images of cracks of concrete decks. This paper describes the development of a support system for decision making in the damage assessment of bridges based on the pattern recognition by using the exception extraction. In this system, the exception extraction with one-class SVM removes some data that may cause the decrease of generalization capability of pattern recognition from the database. Thus, it may be expected that the accuracy and confidence of the results are improved. Numerical examples applying digital images of reinforced-concrete slabs of bridges with cracks are presented to demonstrate the practical use of the approach of this approach. ©Civil-Comp Press, 2013.

关键词： pattern recognition

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Protocol for Site Selection and Movement Assessment for the Myoelectric Control of a Multi-Functional Upper-Limb Prosthesis

Protocol for Site Selection and Movement Assessment for the ...

引用

35th Annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Al-Timemy, Ali H. Escudero, Javier Bugmann, Guido Outram, Nicholas Univ Plymouth Sch Comp & Math Ctr Robot & Neural Syst Plymouth PL4 8AA Devon England

ISBN: (纸本)9781457702167

Although there have been many advances in electromyography (EMG) signal processing and pattern recognition (PR) for the control of multi-functional upper-limb prostheses, some the outstanding problems need to be solved before practical PR-based prostheses can be put into service. Some of these are the lack of training and deployment protocols and the provision of the tools required. Therefore, we present a preliminary procedure to personalize the prosthesis deployment. In the first step, we record the demographic information of each individual amputee person and their background. In the second step of the protocol, the EMG signals are acquired. PR algorithms and parameters will be chosen in the 3rd step of the protocol. In the 4th step, the best number of EMG sensors to achieve the maximal performance with a full set of gestures is identified. The final step involves finding the best set of movements that the amputee person can produce with an accuracy > 95% as well as identifying the movements with the worst performance, which would require further training. This proposed approach is validated with 2 transradial amputees.

关键词： biomechanics biomedical equipment electromyography medical control systems medical signal detection medical signal processing pattern recognition prosthetics sensors

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A Sparse Bayesian Multi-Instance Multi-Label Model for Skin Biopsy Image Analysis

A Sparse Bayesian Multi-Instance Multi-Label Model for Skin ...

引用

IEEE international conference on bioinformatics and Biomedicine (IEEE BIBM)

作者： Zhang, Gang Su, Xiangyang Huang, Yongjing Lao, Yingrong Liang, Zhaohui Ou, Shanxing Huang, Jimmy Guangzhou Gen Hosp Guangzhou Mil Command Dept Radiol Guangzhou 510010 Guangdong Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ 3rd Affiliated Hosp Dept Dermatol & Venerol Guangzhou 510630 Peoples R China Guangzhou Univ Chinese Med 2nd Affiliated Hosp Guangzhou 510120 Peoples R China Cent China Normal Univ Sch Comp Sci Wuhan Peoples R China York Univ Sch Informat Technol Toronto ON Canada

ISBN: (纸本)9781479913091;9781479913107

As a significant complement for skin surface images, skin biopsy image may reveal causes and severity of many skin diseases, especially in the case of skin cancer inspection. With rapid increment of skin disease patients, computational methods have been introduced for automatic classification of skin images. However, due to the complex relationship among annotation terms and features of local regions, it becomes a great challenge for skin biopsy image feature recognition and annotation. In this paper, we attempt to model the potential knowledge and experience of doctors on skin biopsy image annotation by using a recent proposed machine learning model, named multi-instance multi-label (MIML) model. We show that the relationship among annotation terms and skin biopsy images is naturally consistent with the MIML framework. We further propose a sparse Bayesian MIML algorithm which can produce a probability indicating the confidence of annotating a term. The proposed algorithm framework is evaluated on a real dataset from a large local hospital containing 12,700 skin biopsy images. The results show that the proposed algorithm is effective and prominent.

关键词： skin biopsy image annotation normalized cut s-parse bayesian learning mulit-instance multi-label learning gaussian process

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