This Volume 3 of 5 of the conference proceedings contains 225 papers. Topics discussed include global and local motion estimation, communication networks, adaptive signalprocessing, applications of chaos, communicati...
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This Volume 3 of 5 of the conference proceedings contains 225 papers. Topics discussed include global and local motion estimation, communication networks, adaptive signalprocessing, applications of chaos, communicating radio frequency circuits, neural networks, Nyquist data conversion, testing and verification, voltage controlled oscillators and phase locked loops, reference circuits, multimedia watermarking, frequency response masking techniques, VLSI circuit styles, wireless architecture, delta-sigma modulators, translinear and companding filters, vision chips, multidimensional signals and systems, digital circuits synthesis and optimization, video over networks, analysis, design and simulation of power electronics circuits, transforms and multirate systems, wireless LAN design, chaos and information processing, applications of digital signalprocessing in communications, network theory and linear systems, network theory and linear systems, VLSI arithmetic, modeling and analysis of nonlinear systems, low voltage amplifiers, advanced signalprocessing for MIMO systems, imaging architectures, delta-sigma modulators, circuit linearization, analog computing circuits, computational graph theory for computer and communication systems, device and interconnect modeling, video segmentation, DC switching mode power supplies, speech processing, rf filter design and implementation and chaotic communications and signalprocessing.
Disparity estimation is the basis for the generation of virtual view from a small set of real reference images. Much research on this area has been conducted by the computer vision community over the last decade. Curr...
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ISBN:
(纸本)9537044017
Disparity estimation is the basis for the generation of virtual view from a small set of real reference images. Much research on this area has been conducted by the computer vision community over the last decade. Currently, most problems involved in this technology are well understood and there exist several well-established algorithms to render virtual views from perspectivelly different images of the same scene. However, most work has been oriented towards high-accuracy disparity estimation to produce high-quality virtual images, often using sophisticated purpose-built hardware accelerators to achieve real-time results. In this paper two disparity estimators with different complexity degrees are described and used to examine how much disparity inaccuracies influence image rendering quality. The objective of this study is to design software-based image synthesis in real-time on conventional PC platforms. Basically, this work looks at the opposite end of the cost-complexity curve by making very restrained demands to the disparity estimator. It is empirically shown that in many cases the effect of disparity accuracy in the quality of virtual views is almost imperceptible and that for many applications requiring real-time processing reasonable good results can be achieved with less computational cost.
Generally, the more features utilized, the better the retrieval performance. However, it is a very challenging task to combine different feature sets in a way reflecting human perception. This paper presents the combi...
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Generally, the more features utilized, the better the retrieval performance. However, it is a very challenging task to combine different feature sets in a way reflecting human perception. This paper presents the combination of different shape based feature sets using fuzzy integral for leaf image retrieval. The feature sets used in our system include centroid-contour distance curve, eccentricity, and angle code histogram. The fuzzy integral approach can release the user's burden from tuning the combination parameters. In order to reduce the matching time in the retrieval process, a thinning based method is proposed to locate the start point of a leaf contour. Experimental results on 440 leaf images from 44 plant species (10 samples from each plant species) show that the fuzzy integral approach can achieve a comparable retrieval performance with the best case of the weighted summation combination. The results also indicate that our approach, which are more efficient, can achieve a better retrieval performance than both the curvature scale space (CSS) method and the modified Fourier descriptor (MFD) method.
Panoramic mosaics methods based on an 8-parameter planar homography matrix have to overcome the accumulated errors when a sequence of images loops back on itself. Usual methods are computationally intensive, and canno...
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ISBN:
(纸本)9628576623
Panoramic mosaics methods based on an 8-parameter planar homography matrix have to overcome the accumulated errors when a sequence of images loops back on itself. Usual methods are computationally intensive, and cannot ensure complete consistency of homographies. The paper presents a simple method which does not require the consistency of homographies. The method mainly exploits an un-calibrated image perspective interpolation technique (B. Yuan et al., 1998). It is therefore simple to calculate and easy to implement.
This paper presents a solution to the problem of manipulation control: target identification and grasping. The proposed controller is designed for a real platform in combination with a monocular vision system. The obj...
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This paper presents a solution to the problem of manipulation control: target identification and grasping. The proposed controller is designed for a real platform in combination with a monocular vision system. The objective of the controller is to learn an optimal policy to reach and to grasp a spherical object of known size, randomly placed in the environment. In order to accomplish this, the task has been treated as a reinforcement problem, in which the controller learns by a trial and error approach the situation-action mapping. The optimal policy is found by using the Q-Learning algorithm, a model free reinforcement learning technique, that rewards actions that move the arm closer to the target. The vision system uses geometrical computation to simplify the segmentation of the moving target (a spherical object) and determines an estimate of the target parameters. To speed-up the learning time, the simulated knowledge has been ported on the real platform, an industrial robot manipulator PUMA 560. Experimental results demonstrate the effectiveness of the adaptive controller that does not require an explicit global target position using direct perception of the environment.
The proceedings contain 179 papers. The special focus in this conference is on Personal Computer Based Networks of Workstations, Advances in Parallel, Distributed computational Models and Video processing. The topics ...
ISBN:
(纸本)354067442X
The proceedings contain 179 papers. The special focus in this conference is on Personal Computer Based Networks of Workstations, Advances in Parallel, Distributed computational Models and Video processing. The topics include: MPI collective operations over IP multicast;an open market-based architecture for distributed computing;the multicluster model to the integrated use of multiple workstation clusters;parallel information retrieval on an SCI-based pc-now;a pc-now based parallel extension for a sequential DBMS;the heterogeneous bulk synchronous parallel model;a new computation of shape moments via quadtree decomposition;a java applet to visualize algorithms on reconfigurable mesh;a hardware implementation of pram and its performance evaluation;a non-binary parallel arithmetic architecture;multithreaded parallel computer model with performance evaluation;a high performance microprocessor for multimedia computing;a novel superscalar architecture for fast DCT implementation;computing distance maps efficiently using an optical bus;advanced data layout optimization for multimedia applications;parallel parsing of mpeg video in a multi-threaded multiprocessor environment;parallelization techniques for spatial-temporal occupancy maps from multiple video streams;heuristic solutions for a mapping problem in a TV-anytime server network;a programming environment for real-time parallel vision;parallel low-level image processing on a distributed memory system;congestion-free routing of streaming multimedia content in BMIN-based parallel systems;performance of on-chip multiprocessors for vision tasks;specification techniques for automatic performance analysis tools and controlling distributed shared memory consistency from high level programming languages.
A variety of techniques in machine vision involve representation of objects by using their shape skeleton. Many algorithms have been proposed to date for obtaining the skeletal shape of digital images. The noise model...
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A variety of techniques in machine vision involve representation of objects by using their shape skeleton. Many algorithms have been proposed to date for obtaining the skeletal shape of digital images. The noise models predominantly used in these techniques are restricted to boundary noise. In particular, instances of noise occurring inside object regions and causing their non-contiguity are precluded. In this paper we present a method to obtain the skeletal shape of binary images in the presence of both boundary noise and noise occurring inside object regions. We propose to obtain the skeletal shape of such images by a modified version of the Kohonen self-organizing map, implemented in a batch processing mode. The modifications allow the map to adapt to the input shape distribution. At each iteration, a competitive Hebbian rule is used to progressively compute the Delaunay triangulation of the shape. Information from the triangulation augments the map topology to yield the final skeletal shape. The batch mode implementation of the self-organizing process, allows our approach to compare very favorably, in terms of computational time, with the traditional flowthrough implementations. Encouraging experimental performance has been obtained on a variety of shapes under varying signal to noise ratios.
A variety of techniques in machine vision involve representation of objects by using their shape skeleton. In this paper we present a method to obtain the skeletal shape of binary images in the presence of both bounda...
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A variety of techniques in machine vision involve representation of objects by using their shape skeleton. In this paper we present a method to obtain the skeletal shape of binary images in the presence of both boundary noise and noise occurring inside object regions. We propose to obtain the skeletal shape of such images by a modified version of the Kohonen self-organizing map, implemented in a batch processing mode. The modifications allow the map to adapt to the input shape distribution. At each iteration, a competitive Hebbian rule is used to progressively compute the Delaunay triangulation of the shape. Information from the triangulation augments the map topology to yield the final skeletal shape. The batch mode implementation of the self-organizing process, allows our approach to compare very favourably, in terms of computational time, with the traditional flowthrough implementations. Encouraging experimental performance has been obtained on a variety of shapes under varying signal to noise ratios.
In this paper, we define a novel system based on a hierarchical computational and data abstraction model to handle multimedia queries involving face recognition, scene matching, and speech recognition. For this purpos...
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