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International Conference on Intelligent Transportation

作者： B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA

Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.

关键词： Robustness Magnetic heads Vehicle crash testing Sensor systems Stereo vision Layout Statistical analysis Support vector machines Support vector machine classification Vehicle detection

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Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application

Features extraction based on fuzzy clustering and segmentati...

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International Conference on computer Graphics, Imaging and Visualization, CGIV

作者： M.N. Maliki S.A.R.A.B. Al-Attas Computer Vision Video and Image Processing (CVVIP) Research Group Department of Microelectronic and Computer Engineering (MiCE) Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia Computer Vision Universiti Teknologi Malaysia Skudai Johor Malaysia Universiti Teknologi Malaysia Skudai Johor MY Dept. of Microelectron. & Comput. Eng. Univ. Teknologi Malaysia Johor Malaysia

Fuzzy-based clustering algorithm is becoming popular in image processing, especially in image segmentation. Based on the degree of the membership function, each pixel can be grouped into "natural group" of pixels according to the spatial coordinate using their values. In this work we present features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application. Instead of using blob analysis, we believe that fuzzy based clustering algorithm, can also be used to generate different clusters. Incorporating the motion-based segmentation the complexity of the fuzzy clustering is also reduced because only the motion region is processed to the clustering algorithm.

关键词： Feature extraction Surveillance Clustering algorithms image segmentation Equations Prototypes Application software computer vision image processing Data mining

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Building an image-based system to automatically score Psoriasis

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13th Scandinavian Conference on image Analysis, SCIA 2003

作者： Gomez, David Delgado Carstensen, Jens Michael Ersbøll, Bjarne Skov, Lone Bang, Bo Image processing and computer vision Informatics and Mathematical Modelling Richard Petersen Plads Lyngby2800 Denmark Department of dermatology Gentofte hospital Niels Andersenvej 65 Hellerup2900 Denmark

ISBN: (纸本)3540406018

Nowadays the medical tracking of dermatological diseases is imprecise. The main reason is the lack of suitable objective methods to evaluate the lesion. The severity of the disease is scored by doctors just through their visual examination. In this work, a system to take accurate images of dermatological lesions has been developed. Mathematical methods can be applied to these images to obtain values that summarize the lesion and help to track its evolution. The system is composed of two elements. A precise image acquisition equipment and a statistical procedure to extract the lesions from the images. The system is tested on patients with the dermatological disease psoriasis. Temporal series of images are taken for each patient and the lesions are automatically extracted. Results indicate that to the images obtained are a good source for obtaining derived variables to track the lesion. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Discriminant analysis

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An improved edge-model based representation and its application in image post-processing

An improved edge-model based representation and its applicat...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Chi-keung Fong Wai-kuen Cham Computer Vision and Image Processing Electronic Engineering Department Chinese University of Hong Kong New Territories Hong Kong China

ISBN: (纸本)0780376633

images can be represented using as locations and parameters of edges based on an edge mode. The representation was shown to be effective to reduce coding errors of images coded using SPIHT in an image postprocessing method. However, the representation results several artifacts which include "smudge and halos" artifacts and stripping artifacts. We have found the causes of these artifacts and propose a revised representation that has these artifacts significantly suppressed Also, we shall demonstrate that the revised representation can further improve the performance of the image post-processing algorithm.

关键词： image processing Parameter estimation image reconstruction Application software computer vision image coding image storage image converters image edge detection Laboratories

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Video reconstructions in dentistry

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Orthodontics and Craniofacial Research 2003年第SUPPL1期6卷 108-116页

作者： Farag, A.A. Eid, A. Electrical and computer Engineering Department University of Louisville Computer Vision and Image Processing Laboratory Louisville KY 40292 United States

Objectives: To present two practical techniques for threedimensional (3D) modeling of the human jaw from a sequence of intra-oral images. Design: A data acquisition system consists of: 3D digitizing arm, CCD camera and a laser projector in addition to a software module of two 3D modeling techniques;shape from shading (SFS) and space carving (SC). Setting and sample population - Several experiments have been conducted on a sample of students at the computer vision and image processing (CVIP) Laboratory at the University of Louisville, Louisville, KY. Other experiments were performed on solid models of human jaw. Experimental variable: The SFS technique, using perspective projection and camera calibration, extracts the 3D information from a sequence of two-dimensional images of the jaw. Data fusion of range data and 3D registration techniques develop the complete jaw model. The SC approach is implemented on a sequence of calibrated images. On the two reconstructions, we fit a mesh model to the data, in order to create a solid 3D model. Outcome measure: The accuracy of the reconstructed 3D model of human jaw is calculated based on the measurements on real jaws. Results: The SFS-based technique seems to provide more faithful information about the shape of the tooth tops. However, the SC algorithm successfully reconstructed 3D models of the human jaw with sub-millimeter accuracy, which is as accurate as (or even better than) the first technique without using any range measurements or laser projectors. The average error in distance calculation was found to be 0.74 mm, which is an acceptable resolution for many orthodontics and maxillofacial applications. Conclusion: Accurate 3D reconstruction of the human jaw enables many orthodontics and dental imaging researchfindings to be applied directly to a digital jaw model - not to a cast - using computer vision and medical imaging tools. © 2003 Blackwell Munksgaard.

关键词： Data fusion Jaw modeling Registration Shape from shading Space carving

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution(MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Jun, Xie Tsui, H.T. Deshen, Xia Image Processing and Computer Vision Lab Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Pattern Recognition Lab Department of Computer Science Nanjing University of Sci.andTech. China

ISBN: (纸本)0769516963

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties . The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples Its performance in the experiments is better than those of two popular methods. © 2002 IEEE.

关键词： Maximum likelihood estimation

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Head detection and localization from sparse 3D data

Head detection and localization from sparse 3D data

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24th German Association for Pattern Recognition Symposium, DAGM 2002

作者： Clabian, Markus Rötzer, Harald Bischof, Horst Kropatsch, Walter Advanced Computer Vision GmbH Donau City Str.1 ViennaA-1220 Austria Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 GrazA-8010 Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria

ISBN: (纸本)354044209X

Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19x19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images. © Springer-Verlag Berlin Heidelberg 2002.

关键词： computers

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Construction of multi-layer feedforward binary neural network by a genetic algorithm

Construction of multi-layer feedforward binary neural networ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chi Kin Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

An approach is introduced to determine the topology of a feedforward binary neural network automatically. The approach is based on a construction algorithm that constructs one layer of hidden nodes at a time until the problem is solved. In each layer, the algorithm determines the necessary number of nodes through a growth process by finding the best hidden node that would help to partition the input training data set. This is done using a genetic algorithm. The proposed algorithm can determine the necessary number of hidden layers and number of hidden nodes at each layer automatically. Tests on a number of benchmark problems illustrated the effectiveness of the proposed technique, both in terms of network complexity and recognition accuracy, compared with a geometrical learning approach.

关键词： Neural networks Multi-layer neural network Feedforward neural networks Genetic algorithms Network topology Partitioning algorithms Training data Error correction computer vision image processing

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Invariant feature matching by Hopfield-type neural network

Invariant feature matching by Hopfield-type neural network

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International Joint Conference on Neural Networks (IJCNN)

作者： Wen-Jing Li Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

In this paper, a novel Hopfield model for silhouette matching invariant to projective transformations is proposed. Although the new network has higher-order energy function, we show that it can be solved using a standard second-order Hopfield network, by taking advantage of the neighborhood information in the data. The experimental results with real data show that the proposed method can provide accurate matching results in image registration and object recognition.

关键词： Neural networks Hopfield neural networks Object recognition Power engineering and energy Stereo vision Motion estimation Feature extraction Cost function Layout computer vision

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Resolving ambiguity in depth extraction for motion capture using genetic algorithm

Resolving ambiguity in depth extraction for motion capture u...

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Congress on Evolutionary Computation

作者： Yin Yee Wai Chi Kin Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

There is considerable interest in motion capture from an image sequence taken from a video camera. However, since the images only consist of 2D information, the distance of an object from the image plane cannot be determined uniquely unless some constraints are imposed. Coplanar motion is a popular constraint adopted for this purpose. If the captured motion is not coplanar, only two possible solutions can be obtained at the best even the actual size of the object is given. Therefore, the motion cannot be captured without resolving the distances of each control point from the image plane. By assuming smooth transition, the problem is formulated as one minimizing the transition between image frames and the application of GA to solve this optimization problem is proposed.

关键词： Genetic algorithms Humans Cameras image resolution image sequences Animation Motion analysis Optical filters Optical recording Optical sensors

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