Integral projections are a useful technique in many computervision problems. In this paper, we present a perceptual interface which allows us to navigate through a virtual 3D world by using the movements of the face ...
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Active reconstruction of 3D surfaces deals with the control of camer a viewpoints to minimize error and uncertainty in the reconstructed shape of an object. In this paper we develop a mathematical relationship between...
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This paper presents a computervision guidance system for agricultural vehicles. This system is based on a segmentation algorithm that uses an optimum threshold function in terms of minimum quadratic value over a disc...
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ISBN:
(纸本)9783540770459
This paper presents a computervision guidance system for agricultural vehicles. This system is based on a segmentation algorithm that uses an optimum threshold function in terms of minimum quadratic value over a discriminant based on the Fisher lineal discriminant. This system has achieved not only very interesting results in the sense of segmentation, but it has also guided successfully a vehicle in a real world environment.
Several computervision problems, like segmentation, tracking and shape modeling, are increasingly being solved using level set methodologies. But the critical issues of stability and convergence have always been negl...
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Several computervision problems, like segmentation, tracking and shape modeling, are increasingly being solved using level set methodologies. But the critical issues of stability and convergence have always been neglected in most of the level set implementations. This often leads to either complete breakdown or premature/delayed termination of the curve evolution process, resulting in unsatisfactory results. We present a generic convergence criterion and also a means of determining the optimal time-step involved in the numerical solution of the level set equation. The significant improvement in the performance of level set algorithms, as a result of the proposed changes, is demonstrated using object tracking and shape-contour extraction results. (c) 2006 Elsevier B.V. All rights reserved.
Several associative memories (AM) have been proposed in the last years. These AMs have several constraints that limit their applicability in complex problems such as face recognition. Despite of the power of these mod...
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ISBN:
(纸本)9783540767244
Several associative memories (AM) have been proposed in the last years. These AMs have several constraints that limit their applicability in complex problems such as face recognition. Despite of the power of these models, they cannot reach its full power without applying new mechanisms based on current and future studies on biological neural networks. In this research we show how a network of dynamic associative memories (DAM) combined with some aspects of the infant vision system could be efficiently applied to the face recognition problem. Through several experiments by using a benchmark of faces the accuracy of the proposal is tested.
Surface quality is an important characteristic commonly assessed in wood products. Sanding relies on coated abrasives as tooling for both dimensioning and surface finishing, but their performance is dependant on chip ...
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Surface quality is an important characteristic commonly assessed in wood products. Sanding relies on coated abrasives as tooling for both dimensioning and surface finishing, but their performance is dependant on chip loading and grit wear. Traditionally, the useful life of abrasive belts in sanding operations has been manually assessed. This type of inspection is highly dependent upon individual expertise and usually leads to either underutilization or overutilization of the abrasive, which in turn affects the production costs and quality of the product. A classification method that characterizes the abrasive loading curve with artificial neural networks and computervision was developed. Controlled experiments were conducted to develop abrasive belts of known machining exposure. Image processing was complemented with pattern classification and recognition algorithms to support a decision-making framework. The results show 93 percent and 95 percent success rates in abrasive images classification. Also, classification of images from interpolated and extrapolated times of abrasive usage is achieved with high success rates. This approach is proposed as an input to a decision system that would help in evaluating the remaining life of the abrasive and would trigger optimal toot replacements.
vision software packages feature very similar algorithms for processing images, such as pattern matching, particle analysis, optical character recognition (OCR) and 2D barcode readers. The most important feature and b...
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vision software packages feature very similar algorithms for processing images, such as pattern matching, particle analysis, optical character recognition (OCR) and 2D barcode readers. The most important feature and biggest difference between leading vision software packages is the ease with which the algorithms can be used and results communicated. A hypothetical example of an oil filter inspection is used in the paper, where the goal is to identify the oil filter by the number of holes around the centre, verify that an O-ring is present and communicate the results to other industrial devices. vision software packages must be selected by how easily inspection application can be developed and the results communicated to existing equipment.
Principal Components Analysis (PCA), Independent Component Analysis (ICA) and Linear Discriminant Analysis (LDA), have been widely used for 2D face recognition. Local Binary pattern (LBP), however, provides a simpler ...
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ISBN:
(纸本)9781601320438
Principal Components Analysis (PCA), Independent Component Analysis (ICA) and Linear Discriminant Analysis (LDA), have been widely used for 2D face recognition. Local Binary pattern (LBP), however, provides a simpler and more effective way to represent faces. With LBP, face image is divided into small regions from which LBP histograms are extracted and concatenated into a single and global feature histogram representing the face image. The recognition is performed using Chi square and other commonly used dissimilarity measures. In this paper, we construct LBP codes together with three dissimilarity measures on hexagonal structure. We show that LBPs defined on hexagonal structure will lead to a faster and more accurate scheme for face recognition.
Occlusion is currently at the centre of analysis in machine vision. We present an approach to it that uses attention feedback to an occluded object to obtain its correct recognition. Various simulations are performed ...
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Occlusion is currently at the centre of analysis in machine vision. We present an approach to it that uses attention feedback to an occluded object to obtain its correct recognition. Various simulations are performed using a hierarchical visual attention feedback system, based on contrast gain (which we discuss as to its relation to possible hallucinations that could be caused by feedback). We then discuss implications of our results for object representations per se.
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