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Vision, Image and Signal Processing, IEE Proceedings -

Issue 2 • Date 8 April 2005

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Displaying Results 1 - 14 of 14
  • Grey relational analysis based approach for data clustering

    Publication Year: 2005 , Page(s): 165 - 172
    Cited by:  Papers (8)  |  Patents (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (571 KB)  

    This paper generalises the concept of grey relational analysis to develop a technique, called grey relational pattern analysis, for analysing the similarity between given patterns. Based on this technique, a clustering algorithm is proposed for finding cluster centres of a given data set. This approach can be categorised as an unsupervised clustering algorithm because it does not need predetermination of appropriate cluster centres in the initialisation. The problem of determining the optimal number of clusters and optimal locations of cluster centres is also considered. Finally, the approach is used to solve several data clustering problems as examples. In each example, the performance of the proposed algorithm is compared with other well-known algorithms such as the fuzzy c-means method and the hard c-means method. Simulation results demonstrate the effectiveness and feasibility of the proposed method. View full abstract»

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  • Nonlinear blind source separation using a hybrid RBF-FMLP network

    Publication Year: 2005 , Page(s): 173 - 183
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (540 KB)  

    A novel scheme for blind source separation of nonlinearly mixed signals is developed using a hybrid system based on radial basis function (RBF) and feedforward multilayer perceptron (FMLP) networks. In this paper, the development of the proposed RBF-FMLP network is discussed, which hinges on the theory of nonlinear regularisation. The proposed network uses simultaneously local and global mapping bases to perform both signal separation and reconstruction of continuous signals in addition to signals that exhibit a high degree of fluctuation. The parameters of the proposed system are estimated jointly using the generalised gradient descent approach thereby rendering the training process relatively simple and efficient in computation. Simulations of both synthetic and speech signals have been undertaken to verify the efficacy of the proposed scheme in terms of speed, accuracy and robustness against noise. View full abstract»

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  • Decomposition of morphological structuring elements with integer linear programming

    Publication Year: 2005 , Page(s): 148 - 154
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (300 KB)  

    A method is proposed for decomposing morphological structuring elements based on integer linear programming. A decomposition problem is formulated into a set of linear constraints, and an optimal decomposition is a solution to the constraints, obtained by the cutting-plane simplex algorithm. The method has several advantages. It provides a systematic way of decomposing arbitrarily shaped structuring elements. For convex images, factors can be of any size, not restricted to 3 × 3; the candidate set can be freely assigned by the user; and the optimality criteria can be flexible. View full abstract»

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  • Architecture and algorithms for tracking football players with multiple cameras

    Publication Year: 2005 , Page(s): 232 - 241
    Cited by:  Papers (9)  |  Patents (3)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1397 KB)  

    A system architecture and method for tracking people is presented for a sports application. The system input is video data from static cameras with overlapping fields-of-view at a football stadium. The output is the real-world, real-time positions of football players during a match. The system comprises two processing stages, operating on data from first a single camera and then multiple cameras. The organisation of processing is designed to achieve sufficient synchronisation between cameras, using a request-response pattern, invoked by the second stage multi-camera tracker. The single-view processing includes change detection against an adaptive background and image-plane tracking to improve the reliability of measurements of occluded players. The multiview process uses Kalman trackers to model the player position and velocity, to which the multiple measurements input from the single-view stage are associated. Results are demonstrated on real data. View full abstract»

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  • Arbitrary resizing of images in DCT space

    Publication Year: 2005 , Page(s): 155 - 164
    Cited by:  Papers (17)  |  Patents (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (605 KB)  

    Using the spatial relationship of the block discrete cosine transform (DCT) coefficients and subband approximations, algorithms for image halving and doubling operations are presented. The computational steps identified in the process provide a general framework for image resizing operations. Some of the previously reported image halving and doubling algorithms are shown to be special cases. The proposed approach is general enough to accommodate resizing operations with arbitrary factors, namely with integral and rational factors. The application of these methods to the conversion in the compressed domain of images (video frames) from one format to another is demonstrated. View full abstract»

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  • A network of co-operative cameras for visual surveillance

    Publication Year: 2005 , Page(s): 205 - 212
    Cited by:  Papers (13)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1110 KB)  

    A network of co-operative cameras for the visual surveillance of parking lots is presented. Such a network employs multiple subnets able to manage static and active cameras in a hierarchical framework. The system is able to track multiple targets simultaneously and in real-time throughout the controlled areas. The positions of detected objects, computed from different sensors, are fused considering a dynamic reliability factor for each sensor reading. Close-up recordings of suspicious events are obtained by tasking the active camera systems (ACSs). The co-operation is performed through a multicast communication system studied to transmit useful data both intra and inter networks. In particular, information about the position of the object to track, sent by a static camera system (SCS), is used by an ACS to operate an initial repositioning. The ACS compensates background changes owing to the camera motion, detects mobile objects in the scene and autonomously tracks the object of interest. Tracking results are presented in the context of a video surveillance application for a parking lot. View full abstract»

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  • Method for calculating first-order derivative based feature saliency information in a trained neural network and its application to handwritten digit recognition

    Publication Year: 2005 , Page(s): 137 - 147
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (369 KB)  

    A generalised method is presented for calculating the first-order derivative relationship between inputs and outputs in a trained neural network and the use of these derivatives to perform feature selection. We use a handwritten digit data set as a source for comparing this feature selection method with a standard genetic algorithm feature selection method. View full abstract»

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  • EM image segmentation algorithm based on an inhomogeneous hidden MRF model

    Publication Year: 2005 , Page(s): 184 - 190
    Cited by:  Papers (4)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (736 KB)  

    This paper introduces a Bayesian image segmentation algorithm that considers the label scale variability of images. An inhomogeneous hidden Markov random field is adopted in this algorithm to model the label scale variability as prior probabilities. An EM algorithm is developed to estimate parameters of the prior probabilities and likelihood probabilities. The image segmentation is established by using a MAP estimator. Different images are tested to verify the algorithm and comparisons with other segmentation algorithms are carried out. The segmentation results show the proposed algorithm has better performance than others. View full abstract»

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  • Towards automated wide area visual surveillance: tracking objects between spatially-separated, uncalibrated views

    Publication Year: 2005 , Page(s): 213 - 223
    Cited by:  Papers (1)  |  Patents (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2211 KB)  

    This paper presents a solution to the problem of tracking intermittent targets that can overcome long-term occlusions, as well as movement between camera views. Unlike other approaches, our system does not require topological knowledge of the site or labelled training patterns during the learning period. The approach uses the statistical consistency of data obtained automatically over an extended period of time rather than explicit geometric calibration to automatically learn the salient reappearance periods for objects. This allows us to predict where objects may reappear, and within how long. We demonstrate how these salient reappearance periods can be used with a model of physical appearance to track objects between spatially separate regions in single and separated views. View full abstract»

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  • Image analysis architectures and techniques for intelligent surveillance systems

    Publication Year: 2005 , Page(s): 224 - 231
    Cited by:  Papers (9)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (937 KB)  

    Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed, generic and robust. Our second goal is to have a development platform that allows researchers to conceive and easily test new vision algorithms thanks to its modularity and easy set-up. This paper focuses on the image analysis modules. It considers the different kind of inputs, algorithm models in addition to delay and the need of generality. View full abstract»

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  • Editorial. Special section on intelligent distributed surveillance systems

    Publication Year: 2005
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (156 KB)  

    This paper introduces a special section which discusses CCTV systems and video surveillance aspects. View full abstract»

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  • Dual camera intelligent sensor for high definition 360 degrees surveillance

    Publication Year: 2005 , Page(s): 250 - 257
    Cited by:  Papers (10)  |  Patents (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1955 KB)  

    A novel integrated multi-camera video-sensor (panoramic scene analysis PSA) system is proposed for surveillance applications. In the proposed set-up, an omnidirectional imaging device is used in conjunction with a pan tilt zoom (PTZ) camera leading to an innovative kind of sensor that is able to automatically track at a higher zoom level any moving object within the guarded area. In particular, the catadioptric sensor is calibrated and used in order to track every single moving object within its 360 degree field of view. Omnidirectional image portions are eventually rectified and pan, tilt and zoom parameters of the moving camera are automatically adjusted by the system in order to track detected objects. In addition a co-operative strategy was developed for the selection of the object to be tracked by the PTZ sensor in the case of multiple targets. View full abstract»

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  • Intelligent distributed surveillance systems: a review

    Publication Year: 2005 , Page(s): 192 - 204
    Cited by:  Papers (123)  |  Patents (4)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (643 KB)  

    This survey describes the current state-of-the-art in the development of automated visual surveillance systems so as to provide researchers in the field with a summary of progress achieved to date and to identify areas where further research is needed. The ability to recognise objects and humans, to describe their actions and interactions from information acquired by sensors is essential for automated visual surveillance. The increasing need for intelligent visual surveillance in commercial, law enforcement and military applications makes automated visual surveillance systems one of the main current application domains in computer vision. The emphasis of this review is on discussion of the creation of intelligent distributed automated surveillance systems. The survey concludes with a discussion of possible future directions. View full abstract»

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  • Computer vision system for in-house video surveillance

    Publication Year: 2005 , Page(s): 242 - 249
    Cited by:  Papers (7)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (829 KB)  

    In-house video surveillance to control the safety of people living in domestic environments is considered. In this context, common problems and general purpose computer vision techniques are discussed and implemented in an integrated solution comprising a robust moving object detection module which is able to disregard shadows, a tracking module designed to handle large occlusions, and a posture detector. These factors, shadows, large occlusions and people's posture, are the key problems that are encountered with in-house surveillance systems. A distributed system with cameras installed in each room of a house can be used to provide full coverage of people's movements. Tracking is based on a probabilistic approach in which the appearance and probability of occlusions are computed for the current camera and warped in the next camera's view by positioning the cameras to disambiguate the occlusions. The application context is the emerging area of domotics (from the Latin word domus, meaning 'home', and informatics). In particular, indoor video surveillance, which makes it possible for elderly and disabled people to live with a sufficient degree of autonomy, via interaction with this new technology, which can be distributed in a house at affordable costs and with high reliability. View full abstract»

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