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检索条件"机构=Vision and Image Processing Laboratory with the Department of Systems"

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image approximation and smoothing by support vector regression

Image approximation and smoothing by support vector regressi...

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International Joint Conference on Neural Networks (IJCNN)

作者： D. Kai Tik Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

ISBN: (纸本)0780370449

A new image representation by support vector regression (SVR) is introduced. After a grey level image is approximated as a continuous function using SVR, which maps a 2D pixel coordinate input into a 1D pixel grey level output, the image can then be expressed in terms of the extracted support vectors and their corresponding Lagrange multipliers. The image is reconstructed by a linear combination of kernels with weights equal to the values of Lagrange multipliers. With support vector representation, we can observed that: 1) it is able to remove noise from image, the denoising effect of SVR representation is implicit during image encoding, and it can be controlled by the SVR training parameters; 2) if a Gaussian RBF kernel is used in SVR representation, Gaussian smoothing can be easily implemented by increasing the variance of kernel during image reconstruction and sharpening can be done by reducing the variance.

关键词： Smoothing methods Kernel Pixel Vectors Lagrangian functions image reconstruction Noise reduction image representation Gaussian noise image coding

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Optimization on unbounded solution space using dynamic genetic algorithms

Optimization on unbounded solution space using dynamic genet...

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International Joint Conference on Neural Networks (IJCNN)

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

ISBN: (纸本)0780370449

The problem of applying genetic algorithm (GA) to solve an optimization problem over an unbounded solution space is addressed. We propose to first transform the possible range of each parameter in the chromosome to a finite range with a nonlinear mapping such that the search on unbounded solution space becomes a search for high precision solution in a finite range. Modifications on the GA have been found necessary after such nonlinear mapping. As a result, a new GA with dynamic mutation range that facilitates coarse-refine search has been developed.

关键词： Genetic algorithms Biological cells Optimization methods Genetic mutations Computer vision image processing Laboratories Genetic engineering Chromosome mapping Dynamic range

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Lagrange multiplier selection in hybrid video coder control

Lagrange multiplier selection in hybrid video coder control

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IEEE International Conference on image processing

作者： T. Wiegand B. Girod Image Processing Department Heinrich-Hertz-Institut Berlin Germany Information Systems Laboratory University of Stanford Stanford CA USA

Lagrangian coder control with parameter choice is presented that lead to the creation of the new hybrid video coder specifications TMN-10 for H.263 and TML for H.26L. An efficient approach for the determination of the encoding parameters is developed. It is shown by means of experimental results that the Lagrange multiplier for the macroblock mode decision corresponds to the negative slope of the distortion-rate curve of the prediction error coding. This distortion-rate curve is parameterized by the quantization parameter of the DCT coefficients motivating the established dependency with the Lagrange multiplier.

关键词： Lagrangian functions Discrete cosine transforms image coding Quantization Decoding Testing Video compression Bit rate Video coding image processing

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Multi-layer image compression algorithm for e-commerce

Multi-layer image compression algorithm for e-commerce

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IEEE International Conference on systems, Man and Cybernetics

作者： R. Kounchev R. Kouncheva S.H. Rubin M. Milanova Laboratory of Image Processing Technical University of Sofia Sofia Bulgaria Space and Naval Warfare Systems Center San Diego San Diego CA USA Computer Engineering and Computer Science Department University of Louisville Louisville KY USA

A new method for pyramidal image decomposition called inverse is presented. This method permits to obtain first low resolution components while mainly concentrating image energy in these first components. Each one of its components is defined on the basis of approximating models representing the so called oriented surfaces of second degree, which constitute the different levels of the corresponding difference pyramid in the image space with minimum mean-square error (MSE). The inverse pyramidal decomposition (IPD) is compared to the pyramidal structures based on the well-known Laplacian pyramid and to the related reduced pyramids.

关键词： image coding Business image restoration Visualization image quality Laboratories image processing Military computing Computer science USA Councils

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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3rd International Conference on Information Fusion, FUSION 2000

作者： Mostafa, Mostafa G. Farag, Aly A. Essock, Edward Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY 40292 United States Department of Psychology University of Louisville Louisville KY 40292 United States

ISBN: (纸本)2725700000

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results. © 2000 Int. Soc. Inf. Fusion.

关键词： image fusion

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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International Conference on Information Fusion

作者： M.G. Mostafa A.A. Farag E. Essock Department of Electrical and Computer Engineering Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychology University of Louisville Louisville KY USA

关键词： image registration Neural networks Hyperspectral sensors Remote sensing image reconstruction Geometry Remote monitoring Intelligent sensors Satellites Laser radar

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Gesture, speech, and gaze cues for discourse segmentation

Gesture, speech, and gaze cues for discourse segmentation

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Conference on Computer vision and Pattern Recognition (CVPR)

作者： F. Quek D. McNeill R. Bryll C. Kirbas H. Arslan K.E. McCullough N. Furuyama R. Ansari Vision Interfaces and Systems Laboratory Wright State University Dayton OH USA Department of Psychology University of Chicago USA Signal and Image Research Laboratory University of Illinois Chicago USA

Psycholinguistic evidence has established the complementary nature of the verbal and non-verbal aspects of human expression. We present our findings in the detection of these cites in interaction. We use the psycholinguistic device known as the 'catchment' as the locus of integration of gesture, speech and gaze components. We videotape conversation elicitation experiments in which subjects convey complex spatial plans to an interlocutor using a calibrated three-camera setup. We extract the gestural motion of both hands, gaze direction, and voiced units in the discourse and compare these with transcripts generated by expert microanalysis of the video. Our results show the complementary nature of these communicative modalities. Where there is ambiguity in the structure of one modality (such as in haptologies or owing to noise in the audio signal), other modalities provide evidence for correct segmentation.

关键词： Psychology Speech analysis Humans Laboratories Torso Machine vision Motion analysis Speech enhancement Computer vision Video signal processing

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Multi-modal medical volumes fusion by surface matching

Multi-modal medical volumes fusion by surface matching

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5th International Symposium on Signal processing and Its Applications, ISSPA 1999

作者： Eldeib, Ayman M. Yamany, Sameh M. Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville Department of Electrical Engineering Louisville KY 40292 United States

ISBN: (纸本)1864354518

Presents a fast, six degrees of freedom, registration technique to accurately locate the position and orientation of medical volumes (e.g. CT, MRI) with respect to each other for the same patient. The technique uses surface registration and maximization of mutual information. We have developed a novel technique for surface registration which produces highly accurate results when registering two different volumes of the same individual generated from the same modality, such as preoperative MR and intraoperative MR volumes. In case surface registration is not able to accurately register the different volumes, the result is enhanced by multi-modal volume registration. The gain of this combination is to have an accurate alignment and to reduce time needed for registration. For the multi-modal volume registration, the maximization of mutual information (MI) as a matching criterion is used based on genetic algorithms (GA) as a search engine. Our results demonstrate that our registration technique allows for fast, accurate, robust and completely automatic registration of multimodality medical volumes. © 1999 IEEE.

关键词： Genetic algorithms

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Gesture cues for conversational interaction in monocular video

Gesture cues for conversational interaction in monocular vid...

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1999 International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time systems, RATFG-RTS 1999

作者： Quek, Francis McNeill, David Ansari, Rashid Ma, Xin-Feng Bryll, Robert Duncan, Susan McCullough, Karl E. Vision Interfaces and Systems Laboratory Wright State University OH United States Department of Psychology University of Chicago United States Signal and Image Research Laboratory University of Illinois at Chicago United States

ISBN: (纸本)0769503780

We present our work on the determination of cues for discourse segmentation in free-form gesticulation accompanying speech in natural conversation. The basis for this integrating between gesticulation and speech discourse is the psycholinguistic concept of the co-equal generation of gesture and speech from the same semantic intent. We use the psycholinguistic device known as the 'catchment' as the locus around which this integration proceeds. We videotape gesture and speech elicitation experiments in which a subject describes her living space to an interlocutor. We extract the gestural motion of both hands using the Vector Coherence Mapping algorithm that combines spatial, momentum and skin color constraints in parallel using a fuzzy image processing approach. We extract the voiced units in the discourse as F0 units are correlate these with transcribed speech. Psycholinguistics researchers perceptually microanalyze the same video tape to produce a transcript that is annotated with the video timestamp and perceived gesturespeech entities. These serve to direct our high level analysis of the gesture trace and F0 data. We report the results of our analysis that show that the feature of 'handedness' and the kind of symmetry in two-handed gestures provide effective cues for discourse segmentation. We also present observations on how the gesture traces provide cues to segment hand use, high level discourse repair, and super-segmental cues for discourse grouping.

关键词： Catchments

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Object recognition using neural networks and surface signatures

Object recognition using neural networks and surface signatu...

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International Joint Conference on Neural Networks (IJCNN)

作者： S.M. Yamany A.M. El-Bialy A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Systems and Biomedical Engineering Department Cairo University Egypt

We present a concept for 3D free-form object recognition using a surface representation scheme. This representation scheme captures the 3D curvature information of any free-form surface and encodes it into a 2D image corresponding to a certain point on the surface. This image is unique for this point and is independent from the object translation or orientation in space. For this reason we called this image the surface point signature (SPS). Using specially designed neural networks; the SPS images are used in the matching and recognition of 3D objects in a 3D scanned scene.

关键词： Object recognition Neural networks Layout image recognition Shape image processing Laboratories Computer vision Robot vision systems Application software

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