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6th International conference on Informatics, Electronics and vision (ICIEV) / 7th International Symposium in Computational Medical and Health Technology (ISCMHT)

作者： Schaefer, Gerald Loughborough Univ Dept Comp Sci Loughborough Leics England

ISBN: (纸本)9781538610237

pattern classification tasks in digital pathology, which involves the analysis of high resolution digital slides of tissue samples for medical diagnosis, are, like many other medical decision making processes, often imbalanced. this means that there are (many) more training samples of some classes available compared to others, while it is often the minority class(es) that are of medical interest. In this paper, we present strategies for addressing class imbalance in pattern classification problems including the development of cost-sensitive fuzzy classifiers and the derivation of ensemble classification methods, that is classifiers that employ multiple predictors, dedicated for imbalanced classification.

关键词： Medical diagnostic imaging pattern classification Pathology Informatics computer science Task analysis Medical diagnosis pattern recognition Medical diagnosis task analysis computer science pathology Informatics Disease diagnosis diagnostic imaging Classifiers

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Design of A Video-Based Vehicle Speed Measurement System - An Uncertainty Approach 7

Design of A Video-Based Vehicle Speed Measurement System - A...

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Joint 7th International conference on Informatics, Electronics & vision (ICIEV) / 2nd International conference on Imaging, vision and pattern recognition (icIVPR)

作者： Javadi, Saleh Dahl, Mattias Pettersson, Mats, I Kulesza, Wlodek J. Blekinge Inst Technol Dept Math & Nat Sci S-37435 Karlshamn Sweden Blekinge Inst Technol Dept Appl Signal Proc S-37179 Karlskrona Sweden

ISBN: (纸本)9781538651636

Speed measurement is one of the key components of intelligent transportation systems. It provides suitable information for traffic management and law enforcement. this paper presents a versatile and analytical model for a video-based speed measurement in form of the probability density function (PDF). In the proposed model, the main factors contributing to the uncertainties of the measurement are considered. Furthermore, a guideline is introduced in order to design a video-based speed measurement system based on the traffic and other requirements. As a proof of concept, the model has been simulated and tested for various speeds. An evaluation validates the strength of the model for accurate speed measurement under realistic circumstances.

关键词： Intelligent transportation systems machine vision motion analysis pattern recognition speed measurement

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Recognize multi-people interaction activity by PCA-HMMs

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7th Asian conference on computer vision

作者： Wang, Y Hou, XW Tan, TN Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100080 Peoples R China

ISBN: (纸本)3540312196

In this paper, we propose a new approach to multi-people activity recognition in outdoor scenes. the proposed method is based on Hidden Markov Models with parameters of reduced dimensionality. Most existing work is based on HMMs and DBNs, and focuses on the interactions between two objects. However, longer feature vectors of HMMs usually lead to covariance matrix singularity in parameter learning and activity recognition. Moreover, arbitrary structure of DBNs can introduce large computational complexity. Compared with former works, the proposed method named PCA-HMMs reduces the dimensionality of the model parameters while retains most of the original variability, and thus avoids overflowing and weakens the constraints on observations in conventional HMMs. the experimental results proved that the modified HMMs are effective solutions for multi-people interactive activity recognition.

关键词： pattern recognition

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Adversarial network for edge detection 7

Adversarial network for edge detection

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Joint 7th International conference on Informatics, Electronics and vision and 2nd International conference on Imaging, vision and pattern recognition, ICIEV-IVPR 2018

作者： Zeng, Zhiliang Yu, Ying Kin Hong Wong, Kin Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781538651612

Edge detection is a fundamental problem in computer vision and has been explored for many decades. Due to the rapid development of machine learning techniques and their applications to image processing, there is a proliferation of neural network-based approaches to solve the edge detection problem. these methods, such as richer convolutional features for edge detection(RCF), have good performance and even outperform human beings. Most of the existing neural network-based systems use the convolutional network or its variant. they usually produce thick edges and the application of non-maximum-suppression to suppress the edge is necessary. In this paper, we explore another type of neural network called the conditional generative adversarial network (cGAN) to address the edge detection problem. cGAN is an innovative framework to do the image synthesis task. It can generate an image close to the real one. After training, our network can produce an edge map that contains more detailed information and thinner edges compared to the state-of-the-art methods that require the well-known non-maximum-suppression for post-processing. the proposed approach is able to produce a high quality edge map directly without further processing. Our solution is computation efficient. It can achieve a speed of 59 and 26 frames per second (fps) for an image resolution of [256×256×3] and [512×512×3], respectively. © 2018 IEEE.

关键词： Edge detection

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Modelling the effect of view angle variation on appearance-based gait recognition

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7th Asian conference on computer vision

作者： Yu, SQ Tan, DL Tan, TN Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100080 Peoples R China

ISBN: (纸本)3540312196

In recent years, many gait recognition algorithms have been developed, but most of them depend on a specific view angle. However, view angle variation is a significant factor among those that affect gait recognition performance. It is important to find the relationship between the performance and the view angle. In this paper, we discuss the effect of view angle variation on appearance-based gait recognition performance. A multi-view gait database (124 subjects and I I view directions) is created for our research. We propose two models, a geometrical one and a mathematical one, to model the effect of view angle variation on appearance-based gait recognition. these models will be valuable for designing robust gait recognition systems.

关键词： Gait analysis

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An Implicit Spatiotemporal Shape Model for Human Activity Localization and recognition

An Implicit Spatiotemporal Shape Model for Human Activity Lo...

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IEEE-computer-Society conference on computer vision and pattern recognition Workshops

作者： Oikonomopoulos, A. Patras, I. Pantic, M. Univ London Imperial Coll Sci Technol & Med Dept Comp London England Queen Mary Univ London Dept Elect Engn London England

ISBN: (纸本)9781424439942

In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. the main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization of characteristic, sparse, 'visual words' and 'visual verbs'. Evidence for the spatiotemporal localization of the activity are accumulated in a probabilistic spatiotemporal voting scheme. the local nature of our voting framework allows us to recover multiple activities that take place in the same scene, as well as activities in the presence of clutter and occlusions. We construct class-specific codebooks using the descriptors in the training set, where we take the spatial co-occurrences of pairs of codewords into account. the positions of the codeword pairs with respect to the object centre, as well as the frame in the training set in which they occur are subsequently stored in order to create a spatiotemporal model of codeword co-occurrences. During the testing phase, we use Mean Shift Mode estimation in order to spatially segment the subject that performs the activities in every frame, and the Radon transform in order to extract the most probable hypotheses concerning the temporal segmentation of the activities within the continuous stream.

关键词： computer vision

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Real time traffic density measurement using computer vision and dynamic traffic control 7

Real time traffic density measurement using computer vision ...

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Joint 7th International conference on Informatics, Electronics and vision and 2nd International conference on Imaging, vision and pattern recognition, ICIEV-IVPR 2018

作者： Chowdhury, Md. Fahim Ryad Ahmed Biplob, Md. Uddin, Jia Dept. of Computer Science and Engineering BRAC University Dhaka Bangladesh

ISBN: (纸本)9781538651612

In recent times, traffic jam has become a common problem in the major cities all over the world. In this paper, we propose a dynamic traffic control system by measuring the traffic density at the intersections by real time video feeds and image processing. A video sample was collected and then Mixture of Gaussian algorithm was used for background subtraction method and for foreground detection to keep the count of the cars in each lane. the vehicles are detected by their line of centroid. A movement in centroid confirms a vehicle. the traffic lights at the intersections will change dynamically according to the conditions of traffic that will be detected from the video feeds. In between two intersections, there will be multiple cameras installed to count the number of vehicles entering and leaving each intersection. Furthermore, we restrict the vehicles to take right turns in the intersections. To validate our work, density measurement algorithm, images of live feeds and logics for traffic control are shown in this paper. © 2018 IEEE.

关键词： Mixtures

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ROBUST ESTIMATION FOR thE FUNDAMENTAL MATRIX BASED ON LTS AND BUCKETING

ROBUST ESTIMATION FOR THE FUNDAMENTAL MATRIX BASED ON LTS AN...

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7th International conference on Wavelet Analysis and pattern recognition

作者： Huang, Yi-Jun Liu, Wei-Jun Chinese Acad Sci Shenyang Inst Automat Adv Equipment Res & Design Ctr Shenyang 110016 Peoples R China

ISBN: (纸本)9781424437276

the fundamental matrix is an effective tool to analyze epipolar geometry. An accurate solution for obtaining fundamental matrices is the basic requirement in many applications of computer vision. When noises and outliers exist in the set of initial match points, the estimation of the fundamental matrix becomes to a tough mission owing to the invalidation of normal linear and iterative methods. this paper proposes a novel robust technique for estimating the fundamental matrix by combining bucketing technique and the least trimmed squares(LT S) regression into one intelligent algorithm. the new algorithm solves the problem of even distribution of sample data. Also, it eliminates limitations on the proportion of outliers and the requirement a predefined threshold. Comparing with traditional robust methods, the proposed approach is proved to be accuracy and robust by simulation and real image experiments.

关键词： computer vision fundamental matrix robust estimate LTS bucketing technique

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Multispectral face recognition in texture space

Multispectral face recognition in texture space

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7th Canadian conference on computer and Robot vision, CRV 2010

作者： Bendada, Abdelhakim Akhloufi, Moulay A. Computer Vision and Systems Laboratory Laval University Quebec City QC G1V 0A6 Canada

ISBN: (纸本)9780769540405

this work introduces the use of LBP like texture descriptors for efficient multispectral face recognition. LBP has been widely used in visible spectrum face recognition. this work extend its use to non visible spectrums (active and passive infrared spectrums). Local Binary pattern (LBP) and Local Ternary pattern (LTP) descriptors are used. Also a simple differential LTP descriptor (DLT) is introduced. the proposed texture space is less sensitive to noise, illumination change and facial expressions. these characteristics make it a good candidate for efficient multispectral face recognition. Linear and non linear dimensionality reduction techniques are introduced and used for performance evaluation of multispectral face recognition in the texture space. the obtained results show that the use of the proposed texture descriptors permit to achieve high recognition rates in multispectral face recognition. © 2010 IEEE.

关键词： Local binary pattern

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Gesture for video content navigation

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Proceedings of SPIE - the International Society for Optical Engineering 1999年 3656卷 230-242页

作者： Bradski, Gary Yeo, Boon-Lock Yeung, Minerva M. Intel Corp Santa Clara United States

this article describes the use of gesture recognition techniques in computer vision as a natural interface for video content navigation, and the design of a navigation and browsing system that caters to these natural means of computer-human interaction. For consumer applications, video content navigation presents two challenges: (1) how to parse and summarize multiple video streams in an intuitive and efficient manner, and (2) what type of interface will enhance the ease of use for video browsing and navigation in a living room setting or an interactive environment. In this paper, we address the issues and propose the techniques that combine video content navigation with gestures, seamlessly and intuitively, in an integrated system. the current framework can incorporate speech recognition technology. We present a new type of browser for browsing and navigating video content, as well as a gesture recognition interface for this browser.

关键词： pattern recognition

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