We put forth in this paper a geometrically motivated 3D (three-dimensional) motion error analysis, which is capable of supporting investigation of global effect such as inherent ambiguities. The error expression that ...
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ISBN:
(纸本)0769519008
We put forth in this paper a geometrically motivated 3D (three-dimensional) motion error analysis, which is capable of supporting investigation of global effect such as inherent ambiguities. The error expression that we derive allows us to predict the exact conditions likely to cause ambiguities and how these ambiguities vary with motion types such as lateral or forward motion. Our formulation, though geometrically motivated, is employed to model the effect of noise.
We propose a computational model motivated by human cognitive processes for detecting changes of driving environments. The model, called dynamic visual model, consists of three major components: sensory, perceptual, a...
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We propose a computational model motivated by human cognitive processes for detecting changes of driving environments. The model, called dynamic visual model, consists of three major components: sensory, perceptual, and conceptual components. The proposed model is used as the underlying framework in which a system for detecting and recognizing road signs is developed.
We study a pattern in the fingerprint called a crease, a kind of stripe which irregularly crosses the normal fingerprint patterns (ridges and valleys). Creases will cause spurious minutiae when using a conventional fe...
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ISBN:
(纸本)0769519008
We study a pattern in the fingerprint called a crease, a kind of stripe which irregularly crosses the normal fingerprint patterns (ridges and valleys). Creases will cause spurious minutiae when using a conventional feature detection algorithm, and therefore decreases the recognition rate of fingerprint identification. By representing the crease using a parameterized rectangle, we design an optimal filter as a detector. We employ a multi-channel filtering framework to detect creases in different orientations. In each channel, PCA is used to extract a rectangle's parameters from the raw detected results. Our algorithm is demonstrated by experiments.
We describe an algorithm for reconstructing the 3D (three-dimensional) shape of the scene and the relative pose of a number of cameras from a collection of images under the assumption that the scene does not contain p...
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We describe an algorithm for reconstructing the 3D (three-dimensional) shape of the scene and the relative pose of a number of cameras from a collection of images under the assumption that the scene does not contain photometrically distinct "features". We work under the explicit assumption that the scene is made of a number of smooth surfaces that radiate constant energy isotropically in all directions, and setup a region-based cost functional that we minimize using local gradient flow techniques.
This paper investigates critical configurations for projective reconstruction from multiple images taken by a camera moving in a straight line. Projective reconstruction refers to a determination of the 3D (three-dime...
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This paper investigates critical configurations for projective reconstruction from multiple images taken by a camera moving in a straight line. Projective reconstruction refers to a determination of the 3D (three-dimensional) geometrical configuration of a set of 3D points and cameras, given only correspondences between points in the images. A configuration of points and cameras is critical if it cannot be determined uniquely (up to a projective transform) from the image coordinates of the points. It is shown that a configuration consisting of any number of cameras lying on a straight line, and any number of points lying on a twisted cubic constitutes a critical configuration. An alternative configuration consisting of a set of points and cameras all lying on a rational quartic curve exists.
In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based on a color segmentation followed by a ...
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In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based on a color segmentation followed by a region-merging on motion through Markov random fields (MRFs). The technique we propose is inspired by the work of Gelgon and Bouthemy (2000), that has been modified to reduce computational cost in order to achieve a fast segmentation (about ten frame per second). To this aim a modified region matching algorithm (namely partitioned region matching) and an innovative arc-based MRF optimization algorithm with a suitable definition of the motion reliability are proposed. Results on both synthetic and real sequences are reported to confirm validity of our solution.
We present an approach to the recognition of complex-shaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backgrounds to train a classifier cascade ...
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We present an approach to the recognition of complex-shaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backgrounds to train a classifier cascade which determines whether edge pixels in an image belong to an instance of the object or the clutter. Presented with a novel image, we use the cascade to discard clutter edge pixels. The features used for this classification are localized, sparse edge density operations. Experiments validate the effectiveness of the technique for recognition of complex objects in cluttered indoor scenes under arbitrary out-of-image-plane rotation.
This paper presents a representation for three-dimensional objects in terms of affine-invariant image patches and their spatial relationships. Multi-view constraints associated with groups of patches are combined with...
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This paper presents a representation for three-dimensional objects in terms of affine-invariant image patches and their spatial relationships. Multi-view constraints associated with groups of patches are combined with a normalized representation of their appearance to guide matching and reconstruction, allowing the acquisition of true three-dimensional affine and Euclidean models from multiple images and their recognition in a single photograph taken from an arbitrary viewpoint. The proposed approach does not require a separate segmentation stage and is applicable to cluttered scenes. Preliminary modeling and recognition results are presented.
We illustrate how to consider a network of cameras as a single generalized camera in a framework proposed by Nayar (2001). We derive the discrete structure from motion equations for generalized cameras, and illustrate...
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We illustrate how to consider a network of cameras as a single generalized camera in a framework proposed by Nayar (2001). We derive the discrete structure from motion equations for generalized cameras, and illustrate the corollaries to epipolar geometry. This formal mechanism allows one to use a network of cameras as if they were a single imaging device, even when they do not share a common center of projection. Furthermore, an analysis of structure from motion algorithms for this imaging model gives constraints on the optimal design of panoramic imaging systems constructed from multiple cameras.
作者:
A.F. KoschanImaging
Robotics and Intelligent Systems Laboratory University of Tennessee Knoxville Tennessee
In this paper, we describe an algorithm called fast marching watersheds that segments a triangle mesh into visual parts. This computervision algorithm leverages a human vision theory known as the minima rule. Our imp...
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In this paper, we describe an algorithm called fast marching watersheds that segments a triangle mesh into visual parts. This computervision algorithm leverages a human vision theory known as the minima rule. Our implementation computes the principal curvatures and principal directions at each vertex of a mesh, and then our hill-climbing watershed algorithm identifies regions bounded by contours of negative curvature minima. These regions fit the definition of visual parts according to the minima rule. We present evaluation analysis and experimental results for the proposed algorithm.
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