Me consider the expression and recognition of dynamic concepts by regarding the movement patterns learned in a recurrent neural net as symbols. We then develop a method to express more abstract dynamic concepts by com...
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ISBN:
(纸本)0780374614
Me consider the expression and recognition of dynamic concepts by regarding the movement patterns learned in a recurrent neural net as symbols. We then develop a method to express more abstract dynamic concepts by combining them with symbols and connecting several recurrent neural networks. Application of the method to actual recognition cases, ball bouncing and dancing, demonstrated its effectiveness. These experiments showed the ability of the method to deal with dynamic concepts that are difficult to describe because of vagueness.
In this paper we focus on selection of relevant features and examples, which is one of the central problems in machine learning and patternrecognition. We describe a way of selecting all combinations of relevant, irr...
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In this paper we focus on selection of relevant features and examples, which is one of the central problems in machine learning and patternrecognition. We describe a way of selecting all combinations of relevant, irr...
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The problem of tree pattern matching for object recognition in images is computationally intensive in nature. In two-dimensional images, the objects can be represented through multiscale decomposition as tree structur...
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ISBN:
(纸本)0769517129
The problem of tree pattern matching for object recognition in images is computationally intensive in nature. In two-dimensional images, the objects can be represented through multiscale decomposition as tree structures. The pattern tree representing an object can be matched with a subject tree representing an image in order to detect the objects within the image. In this paper, we describe a new systolic algorithm and its realization as a VLSI chip for tree pattern matching. The hardware algorithm is based on a linear array of processing.elements (PEs) where the pattern matching is done in a pipelined fashion relying on nearest-neighbor communication between the PE's and the subject and pattern trees of arbitrary length can be processed using a fixed size PE array. The algorithm has an improved execution time of O([m/a](n)) required to perform the matching where m, a and n are the sizes of the pattern tree, processor array, subject tree respectively. A prototype CMOS VLSI chip implementing the proposed algorithm has been designed and verified It is shown that the hardware algorithm proposed in this work represent a significant improvement in terms of computational complexity, data flow, and architecture over the ones previously proposed for this problem.
In this paper we study and compare the recognition performance of subspaces in two different spaces, namely the image space and spectral histogram space. In image space, each image is represented as a long vector and ...
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In this paper we study and compare the recognition performance of subspaces in two different spaces, namely the image space and spectral histogram space. In image space, each image is represented as a long vector and in the spectral histogram space, each image is represented by its histograms of the convolved images with a chosen bank of filters. Spectral histogram space is a nonlinear transformation of the image space. First principal components and independent components in the spaces are studied. Then we study different subspaces by connecting the known subspaces through geodesic curves in the projection space. Our preliminary results show the recognition performance depends more on which space to use than the different subspaces in a given space. This suggests the need to study different spaces for recognition purpose.
This Volume II of III of the conferenceproceedings contains 244 papers. Topics discussed include video technologies for set-top boxes, scalable video coding, segmentation, facial recognition and detection, watermarki...
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This Volume II of III of the conferenceproceedings contains 244 papers. Topics discussed include video technologies for set-top boxes, scalable video coding, segmentation, facial recognition and detection, watermarking, image and video transmission over networks, stereoscopic and three dimensional coding, motion detection and estimation, imageprocessing. color and multispectral processing. video segmentation and indexing, reconstruction techniques and analysis, video coding standards, computer vision, image retrieval, tomographic imaging, error concealment and protection, enhancement and restoration and watermarking.
The purpose of the work reported here is to show that spectral information could be used with high efficiency in various science investigations. The results obtained allow to describe the procedure of forming chromati...
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ISBN:
(纸本)0819447145
The purpose of the work reported here is to show that spectral information could be used with high efficiency in various science investigations. The results obtained allow to describe the procedure of forming chromaticity windows with minimum dimensions preassigned by probabilities of correct identification of image elements by their chromaticities. The ability of a color camera to distinguish small chromaticity differences for image processors have been discussed. These data are important in many applications of color computer vision systems. A multispectral imageprocessing.automated system were developed for and applied to the analytical methods that have been used for several years to control the ecological and biological processes.
This Volume 4875 Part 2 of 2 parts of the conferenceproceedings contains 75 papers. Topics discussed include patternrecognition, character recognition, speech recognition, image segmentation, feature extraction, com...
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This Volume 4875 Part 2 of 2 parts of the conferenceproceedings contains 75 papers. Topics discussed include patternrecognition, character recognition, speech recognition, image segmentation, feature extraction, computer vision, graphics (model and generation, animation and visualization), multimedia database, multimedia information and virtual reality.
There is currently a considerable interest in methods of invariant 3D imagerecognition. Indeed, very often information about 3D objects can be obtained by computer tomographic reconstruction, 3D magnetic resonance im...
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ISBN:
(纸本)081944488X
There is currently a considerable interest in methods of invariant 3D imagerecognition. Indeed, very often information about 3D objects can be obtained by computer tomographic reconstruction, 3D magnetic resonance imaging, passive 3D sensors or active range finders. Due to that algorithms of systematic derivation of 3D moment invariants should be developed for 3D colour object recognition. In this work we proposed an elegant theory which allows to describe many such invariants. Our theory is based on the theory of triplet numbers and quaternions. We propose Hurwitzon valued invariants, which are related to the descriptions of objects as the zero sets of implicit polynomials. These are global invariants which show great promise for recognition of complicated objects. Hurwitzon-valued invariants have good discriminating power for computerrecognition of 3D colour objects using statistical patternrecognition methods. For fast computation of Hurwitzon-valued invariants we us(, modular arithmetic of Galois fields and rings, which maps calculation of invariants to fast number theoretical Fourior-Galois-Hamilton transform.
An emotion recognition system based on processing.of multiple physiological signals is presented. Our algorithm is developed and verified based on multiple subjects by presenting multimodal stimuli that were elaborate...
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An emotion recognition system based on processing.of multiple physiological signals is presented. Our algorithm is developed and verified based on multiple subjects by presenting multimodal stimuli that were elaborated to effectively induce emotions, and thus not dependent on single specific user. The system utilizes physiological signals that can be acquired without discomfort from body surface. Support vector machine was introduced as pattern classifier to overcome the difficulty of large overlap among clusters and large variance within cluster. Correct classification ratio was 77.8 and 61.2%, for emotion recognition problem of three and four categories, respectively. Another advantage of our system is that it requires shorter signal monitoring time than previous ones, and thus better suited for practical use.
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