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检索条件"主题词=change detection algorithms"

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detection and Tracking of Multiple Moving Objects in Real-World Scenarios using Attributed Relational Graph

Detection and Tracking of Multiple Moving Objects in Real-Wo...

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Canadian Conference on Computer and Robot Vision, CRV

作者： Wei Huang Q.M. Jonathan Wu Department of Electrical and Computer Engineering University of Windsor Windsor ONT Canada

This paper presents a new algorithm for detecting and tracking multiple moving objects in both outdoor and indoor environments. The proposed method measures the change of a combined color-texture feature vector in each image block to detect moving objects. The texture feature is extracted from DCT frequency domain. An attributed relational graph (ARG) is used to represent each object, in which vertices are associated to an objectpsilas sub-regions and edges represent spatial relations among them. Multiple cues including color, texture, and spatial position are integrated to describe each objectpsilas sub-regions. Object tracking and identification are accomplished by inexact graph matching, which enables us to track partially occluded objects and to cope with object articulation. An ARG adaptation scheme is incorporated into the system to handle the changes in object scale and appearance. The experimental results prove the efficiency of the proposed method.

关键词： Object detection Motion detection Hidden Markov models Active shape model Computer vision change detection algorithms Indoor environments Tracking Principal component analysis Object recognition

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Face pose estimation and tracking using automatic 3D model construction

Face pose estimation and tracking using automatic 3D model c...

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Pedro Jimenez Jesus Nuevo Luis M. Bergasa Department of Electronics University of Alcala Alcala de Henares Spain

This paper presents a method for robustly tracking and estimating the face pose of a person in both indoor and outdoor environments. The method is invariant to identity and that does not require previous training. A face model is automatically initialized and constructed on-line, when the face is frontal to the stereo camera system. To build the model, a fixed point distribution is superposed over the frontal face, and several appropriate points close to those locations are chosen for tracking. Using the stereo correspondence of the two cameras, the 3D coordinates of these points are extracted, and the 3D model is created. RANSAC and POSIT are used for tracking and 3D pose calculation at each frame. The approach runs in real time, and has been tested on sequences recorded in the laboratory and in a moving car.

关键词： Face detection Cameras Testing Eyes Robustness Support vector machines Computer vision change detection algorithms Application software Stereo vision

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Person tracking on a mobile robot with heterogeneous inter-characteristic feedback

Person tracking on a mobile robot with heterogeneous inter-c...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Juhyun Lee Peter Stone Department of Computer Sciences University of Texas Austin USA

For a mobile robot that interacts with humans such as a home assistant or a tour guide robot, tracking a particular person among multiple persons is a fundamental, yet challenging task. Uniquely identifying characteristics such as a person's face, may not be visible consistently enough to be used as the sole form of identification. Rather, it may be useful to also track more frequently visible, but perhaps less uniquely identifying characteristics such as a person's clothes. After learning various characteristics of a person, the tracking system is required to autonomously update itself with additional training data, since the learned features may change over space and time due to the mobile nature of the robot. In this paper, we introduce a novel algorithm for merging multiple, heterogeneous sub-classifiers designed to track and associate different characteristics of a person being tracked. These heterogeneous classifiers give feedback to each other by identifying additional online training data for one another, thus improving the performance of each classifier and the accuracy of the overall system. Our algorithm has been fully implemented and tested on a Segway base.

关键词： Mobile robots Feedback Training data Orbital robotics Human robot interaction Face detection Testing change detection algorithms Robotics and automation USA Councils

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A new adaptive control algorithm for maximum power point tracking for wind energy conversion systems

A new adaptive control algorithm for maximum power point tra...

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Annual IEEE Conference on Power Electronics Specialists (PESC)

作者： Joanne Hui Alireza Bakhshai Energy and Power Electronics Applied Research Laboratory (PEARL) Queen's University Kingston Canada

This paper presents a new adaptive control algorithm for maximum power point tracking (MPPT) in wind energy systems. A mathematical model of a wind turbine system is also provided. The proposed control algorithm allows the generator to track the optimal operation points of the wind turbine system under fluctuating wind conditions and the tracking process speeds up over time. This algorithm does not require the knowledge of intangible turbine mechanical characteristics such as its power coefficient curve, power characteristic or torque characteristic. It employs a search and reuse concept, a modified Hill Climb Searching (HCS) method and two newly defined loops: change detection loop (CDL) and operation point adjustment loop (OPAL). The adaptive nature of the proposed algorithm eliminates the need for customized algorithms that are optimal for only one particular turbine. It is also a solution to achieve fast optimum power point detection after its initial learning process. A simulated system has been built in PSIM 7.0 for mathematical verification of the wind energy system and for the verification of the proposed algorithm. The algorithm is realized in C++ script and detailed descriptions of the proposed control algorithm are provided for illustration purposes.

关键词： Wind turbines Optimized production technology Wind speed Wind energy Generators Mathematical model change detection algorithms

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Foundations of Adaptive Data Stream Mining for Mobile and Embedded Applications

Foundations of Adaptive Data Stream Mining for Mobile and Em...

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Cairo International Biomedical Engineering Conference, CIBEC

作者： Mohamed Medhat Gaber Centre for Distributed Systems and Software Engineering Monash University Melbourne Australia

Mining data streams for mobile and embedded applications faces a major problem represented in the high rate of the streaming input with regard to the available computational resources. Adapting the data mining algorithms to the availability of resources is an essential step towards realizing the potential applications in this area. In this paper, we review our Algorithm Output Granularity (AOG) for data stream mining adaptation. The generalization of AOG based on Probably Approximately Correct (PAC) learning model is presented. This generalization is of paramount importance to establish a theoretical framework for adaptation and resource-awareness in data stream mining.

关键词： Data mining Machine learning Availability change detection algorithms Clustering algorithms Machine learning algorithms Mobile computing Application software Software engineering Electronic mail

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A Distributed Algorithm for Critical Area detection in Satellite Imagery

A Distributed Algorithm for Critical Area Detection in Satel...

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International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Razvan Alecsandrescu Florin Pop Valentin Cristea Faculty of Automatics and Computer Science University Politehnica of Bucharest Romania

This paper presents a distributed algorithm for critical area detection in satellite imagery. The detection of critical area is very important in natural disaster detection and control. The algorithm uses the distributed change detection methods for multiple spectral bands in satellite images and combines changes which have appeared during a period of time. The result shows a critical area for analyzed time interval. The algorithm is distributed for support a large amount of data. The distributed approach shows a decrease in processing time with the increase of the number of workers. The presented algorithm represents a component from MedioGRID system, which implemented a real-time satellite image processing system for extracting relevant environmental and meteorological parameters on Grid systems. The critical area detection application will be integrated in Grid environments.

关键词： Distributed algorithms Satellites change detection algorithms Clustering algorithms Earthquakes detection algorithms Grid computing Iterative algorithms Image processing MODIS

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An automatic method to learn and transfer the photometric appearance of partially overlapping images

An automatic method to learn and transfer the photometric ap...

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IEEE International Conference on Image Processing

作者： Marco Zuliani Luca Bertelli B. S. Manjunath Mayachitra Inc. Santa Barbara CA USA Electrical and Computer Engineering Department University of California Santa Barbara CA USA

The first major contribution of this paper is a robust method to learn the photometric mapping between the overlapping portions of two registered images acquired either under different lighting conditions or different sensor modalities. Then, once such mapping is learnt, we demonstrate how it generalizes so that the photometric appearance can be transferred from one image to the other out of their overlapping area. This task is fundamental in several different contexts, such as image colorization, seamless mosaicking or change detection. After introducing the theory and discussing the algorithms, we will present several examples that confirm the efficacy of the proposed method in dealing with different types of images.

关键词： Photometry Robustness Image registration Image sensors change detection algorithms Function approximation Pixel Performance gain Rendering (computer graphics) Infrared imaging

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ReDSOM: Relative Density Visualization of Temporal changes in Cluster Structures Using Self-Organizing Maps

ReDSOM: Relative Density Visualization of Temporal Changes i...

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IEEE International Conference on Data Mining (ICDM)

作者： Denny Graham J. Williams Peter Christen Faculty of Computer Science University of Indonesia Indonesia Department of Computer Science Australian National University Canberra Australia Australian Taxation Office Canberra Australia

We introduce a self-organizing map (SOM) based visualization method that compares cluster structures in temporal datasets using relative density SOM (ReDSOM) visualization. Our method, combined with a distance matrix-based visualization, is capable of visually identifying emerging clusters, disappearing clusters, enlarging clusters, contracting clusters, the shifting of cluster centroids, and changes in cluster density. For example, when a region in a SOM becomes significantly more dense compared to an earlier SOM, and well separated from other regions, then the new region can be said to represent a new cluster. The capabilities of ReDSOM are demonstrated using synthetic datasets, as well as real-life datasets from the World Bank and the Australian Taxation Office. The results on the real-life datasets demonstrate that changes identified interactively can be related to actual changes. The identification of such cluster changes is important in many contexts, including the exploration of changes in population behavior in the context of compliance and fraud in taxation.

关键词： Self organizing feature maps Data mining Data visualization Computer science Supervised learning change detection algorithms Data analysis Australia Government Degradation

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Automatic hand trajectory segmentation and phoneme transcription for sign language

Automatic hand trajectory segmentation and phoneme transcrip...

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International Conference on Automatic Face and Gesture Recognition

作者： W.W. Kong Surendra Ranganath Department of Electrical and Computer Engineering National University of Singapore Singapore

This paper presents an automatic approach to segment 3-D hand trajectories and transcribe phonemes based on them, as a step towards recognizing American sign language (ASL).We first apply a segmentation algorithm which detects minimal velocity and maximal change of directional angle to segment the hand motion trajectory of naturally signed sentences. This yields over-segmented trajectories, which are further processed by a trained naive Bayesian detector to identify true segmented points and eliminate false alarms. The above segmentation algorithm yielded 88.5% true segmented points and 11.8% false alarms on unseen ASL sentence samples. These segmentation results were refined by a simple majority voting scheme, and the final segments obtained were used to transcribe phonemes for ASL. This was based on clustering PCA-based features extracted from training sentences. We then trained hidden Markov models (HMMs) to recognize the sequence of phonemes in the sentences. On the 25 test sentences containing 157 segments, the average number of errors obtained was 15.6.

关键词： Handicapped aids change detection algorithms Hidden Markov models Motion detection Bayesian methods Detectors Clustering algorithms Voting Feature extraction Testing

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Modified DMAC Clustering Algorithm for VANETs

Modified DMAC Clustering Algorithm for VANETs

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International Conference on Systems and Networks Communications (ICSNC)

作者： Grzegorz Wolny Research and Development Centre Branch Telekomunikacja Polska Warsaw Poland

In this paper a new clustering algorithm for vehicular ad-hoc networks (VANET) is presented. The proposed solution is a modification of the Basagnipsilas distributed and mobility-adaptive clustering (DMAC) algorithm. Some additional conditions that have to be fulfilled before the cluster head change, are introduced to better suit the road traffic. Tests performed in the simulation environment consisting of VanetMobiSim and JiST/SWANS++ show that algorithm performs better than the original solution - the clusters stability is significantly increased.

关键词： Clustering algorithms Roads Ad hoc networks Telecommunication traffic change detection algorithms Topology Current measurement Velocity measurement Performance evaluation Stability

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