This paper presents a general formulation enabling construction of all functions that are steerable under any transformation group. The method is based on a Lie-group theoretic approach.
ISBN:
(纸本)0818672587
This paper presents a general formulation enabling construction of all functions that are steerable under any transformation group. The method is based on a Lie-group theoretic approach.
This paper is concerned with acquiring panoramic focused images using a small field of view video camera. When scene points are distributed over a range of distances from the sensor, obtaining a focused composite imag...
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ISBN:
(纸本)0818672587
This paper is concerned with acquiring panoramic focused images using a small field of view video camera. When scene points are distributed over a range of distances from the sensor, obtaining a focused composite image involves focus computations and mechanically changing some sensor parameters (translation of sensor plane, panning of camera etc.) which can be time intensive. In this paper we present methods to optimize the image acquisition strategy in order to reduce redundancy. We show that panning a camera about a point f (focal length) in front of the camera eliminates redundancy. The Non-frontal imaging camera (NICAM) with tilted sensor plane has been previously introduced as a sensor that can acquire focused panoramic images. In this paper we also describe strategies for optimal selection of panning angle increments and sensor plane tili for NICAM. Experimental results are presented for panoramic image acquisition using a regular camera as well as using NICAM.
A least-squares method simultaneously solves for the model-to-sensor-suite pose and sensor-to-sensor registration. The development is for a sensor-suite containing separate range and optical sensors. To address outlie...
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ISBN:
(纸本)0818672587
A least-squares method simultaneously solves for the model-to-sensor-suite pose and sensor-to-sensor registration. The development is for a sensor-suite containing separate range and optical sensors. To address outliers and, more generally, match finding, a statistical method (median filtering) and a search method (local search) are developed. Sensitivity to Gaussian noise and the choice of initial pose estimates is investigated on synthetic data. Both of the matching methods are demonstrated on real data.
A framework for object segmentation in vector-valued images is presented in this paper. The first scheme proposed is based on geometric active contours moving towards the objects to be detected in the vector-valved im...
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ISBN:
(纸本)0818672587
A framework for object segmentation in vector-valued images is presented in this paper. The first scheme proposed is based on geometric active contours moving towards the objects to be detected in the vector-valved image. Objects boundaries are obtained as geodesics or minimal weighted distance curves in a Riemannian space. The metric in this space is given by a definition of edges in vector-valued images. The curve flow corresponding to the proposed active contours holds formal existence, uniqueness, stability, and correctness results. The techniques is applicable for example to color and texture images. The scheme automatically handles changes in the deforming curve topology. We conclude the paper presenting an extension of the color active contours which leads to a possible image flow for vector-valued image segmentation. The algorithm is based on moving each one of the image level-sets according to the proposed color active contours. This extension also shows the relation of the color geodesic active contours with a number of partial-differential-equations based imageprocessing.algorithms as anisotropic diffusion and shock filters.
A Multiple Instruction Multiple Data (MIMD) parallel computing platform built upon a network of TMS320C40/44s (C40/C44) for real-time imageprocessing.of a hierarchical foveal machine vision (HFMV) system is described...
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A Multiple Instruction Multiple Data (MIMD) parallel computing platform built upon a network of TMS320C40/44s (C40/C44) for real-time imageprocessing.of a hierarchical foveal machine vision (HFMV) system is described in this paper. The architecture of the system, the parallel algorithm development environment, and strategies to map tasks into the computing platform are described. The platform supports both static and dynamic computing resource allocation. The performance of the computing platform is illustrated by examples.
Historically, SSD or correlation-based visual tracking algorithms have been sensitive to changes in illumination and shading across the target region. This paper describes methods for implementing SSD tracking that is...
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Historically, SSD or correlation-based visual tracking algorithms have been sensitive to changes in illumination and shading across the target region. This paper describes methods for implementing SSD tracking that is both insensitive to illumination variations and computationally efficient. We first describe a vector-space formulation of the tracking problem, showing how to recover geometric deformations. We then show that the same vector space formulation can be used to account for changes in illumination. We combine geometry and illumination into an algorithm that tracks large image regions on live video sequences using no more computation than would be required to track with no accommodation for illumination changes. We present experimental results which compare the performance of SSD tracking with and without illumination compensation.
We present the concept of non-rigid matching based on demons, by reference to Maxwell's demons. We contrast this concept with the more conventional viewpoint of attraction. We show that demons and attractive point...
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We present the concept of non-rigid matching based on demons, by reference to Maxwell's demons. We contrast this concept with the more conventional viewpoint of attraction. We show that demons and attractive points are clearly distinct for large deformations, but also that they become similar for small displacements, encompassing techniques close to optical flow. We describe a general iterative matching method based on demons, and derive from it three different non-rigid matching algorithms, one using all the image intensities, one using only contours, and one for already segmented images. At last, we present results with synthesized and real deformations, with applications to computer Vision and Medical imageprocessing.
The use of visual representations in which retinal neurons receptive fields are not constant over the visual field is universal in the visual systems of higher vertebrates, and is coming to play an important role in a...
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The use of visual representations in which retinal neurons receptive fields are not constant over the visual field is universal in the visual systems of higher vertebrates, and is coming to play an important role in active vision applications. The breaking of translation symmetry that is unavoidably associated with non-uniform sampling presents a major algorithmic complication for imageprocessing. In this paper we use a Lie group approach to derive a kernel which provides a quasi-shift (i.e. approximate shift) invariant template matching capability, under normal convolution in the distorted (range) coordinates of the non-uniform mapping. We work out the special case of the log-polar mapping, which is of great interest in vision; in this case, we call the associated linear integral transform the "exponential chirp transform" (ECT). The method is, however, general for other forms of mapping, or warp, function.
Steerable functions find application in numerous problems in imageprocessing.computer vision and computer graphics. As such, it is important to develop the appropriate mathematical tools to analyze them. In this pap...
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Steerable functions find application in numerous problems in imageprocessing.computer vision and computer graphics. As such, it is important to develop the appropriate mathematical tools to analyze them. In this paper, we introduce the mathematics of Lie group theory in the context of steerable functions and present a canonical decomposition of these functions under any transformation group. The theory presented in this paper can be applied and extended in various ways.
The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this pa...
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The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this paper we present a new approach which successfully solves these problems. The major novelty of our approach lies in the way how the coefficients of the eigenimages are determined. Instead of computing the coefficients by a projection of the data onto the eigenimages, we extract them by a hypothesize-and-test paradigm using subsets of image points. Competing hypotheses are then subject to a selection procedure based on the Minimum Description Length principle. The approach enables us not only to reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.
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