We examine the use of a multi-stage diffusion process in early processing of range data. The input range data is interpreted as occupying a volume in 3-D space. Each diffusion stage simulates the process of diffusing ...
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ISBN:
(纸本)081863880X
We examine the use of a multi-stage diffusion process in early processing of range data. The input range data is interpreted as occupying a volume in 3-D space. Each diffusion stage simulates the process of diffusing part of the boundary of the volume into the volume. The outcome of the process can be used for both discontinuity detection and segmentation into shape homogeneous regions. The process is applied to synthetic noise-free and noisy-step, roof, and valley edges, as well as real range images.
The overall movement of articulated bodies (such as the human body) is enabled by the coordinated movement of its rigid body parts. The body parts are connected by joints and, in general, move differently. For, interp...
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ISBN:
(纸本)081863880X
The overall movement of articulated bodies (such as the human body) is enabled by the coordinated movement of its rigid body parts. The body parts are connected by joints and, in general, move differently. For, interpreting these movements as the movement of one single body, it seems to be necessary to incorporate knowledge in the analysis process. Therefore, in order to recognize pedestrians from monocular image sequences, we introduce a model-based approach. We represent the human body by a volume model and use medical motion data for simulating the movement of walking. This knowledge is exploited to determine the 3D-position as well as the posture of an observed person. By applying a Kalman filter we incrementally estimate the model parameters in consecutive images. Our approach has been tested on real image data.
An approach to labeling the components of human faces from range images is proposed. The components of interest are those humans usually find significant for recognition. To cope with the non-rigidity of faces, a qual...
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ISBN:
(纸本)081863880X
An approach to labeling the components of human faces from range images is proposed. The components of interest are those humans usually find significant for recognition. To cope with the non-rigidity of faces, a qualitative approach is used. The preprocessing stage employs a multi-stage diffusion process to identify convexity and concavity points. These points are grouped into components and qualitative reasoning about possible interpretations of the components is performed. Consistency of hypothesized interpretations is carried out using context-based reasoning. Experimental results on real range images of several faces are provided.
This paper is devoted to spatio-temporal segmentation in echocardiographic images sequences. We combine spatial properties and temporal properties in order to compute segmentation and tracking in a single process. The...
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ISBN:
(纸本)081863880X
This paper is devoted to spatio-temporal segmentation in echocardiographic images sequences. We combine spatial properties and temporal properties in order to compute segmentation and tracking in a single process. The MRF framework is used for modeling the energy function because it allows one to make use simultaneously of local properties, global information, and temporal regularity. Starting from a reference image, where a manual segmentation is made, we develop a method to estimate the model parameters. Such estimation is a crucial point in MRF models. Thus, given an initial segmentation of the sequence, this approach can segment and track a cardiac cavity during the cardiac cycle. We demonstrate its performance on a real echocardiographic sequence.
This paper gives a new method for image rectification, the process of resampling pairs of stereo images taken from widely differing viewpoints in order to produce a pair of `matched epipolar projections'. These ar...
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ISBN:
(纸本)081863880X
This paper gives a new method for image rectification, the process of resampling pairs of stereo images taken from widely differing viewpoints in order to produce a pair of `matched epipolar projections'. These are projections in which the epipolar lines run parallel with the x-axis and consequently, disparities between the images are in the x-direction only. The method is based on an examination of the essential matrix of Longuet-Higgins which describes the epipolar geometry of the image pair. The approach taken is consistent with that recently advocated strongly by Faugeras of avoiding camera calibration. We define a matrix called the `epipolar transformation matrix' which is used to determine a pair of 2D projective transforms to be applied to the two images in order to match the epipolar lines. The advantages include the simplicity of the 2D projective transformation which allows very fast resampling as well as subsequent simplification in the identification of matched points and scene reconstruction.
We introduce a computational framework for matching a pair of stereo images which, in contrast to existing algorithms, features a self-contained local matching module cascaded with a global matching module. Local matc...
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ISBN:
(纸本)081863880X
We introduce a computational framework for matching a pair of stereo images which, in contrast to existing algorithms, features a self-contained local matching module cascaded with a global matching module. Local matching outputs a 3D grey-scale image in which each and every point has an intensity measuring the goodness a possible match. As such global matching reduces to surface detection in this image. To detect the surface we first enhance it employing a hyper-pyramid data structure. Unlike traditional multiresolution approaches, which are based on the coarse-to-fine continuation method, our multilevel method emphasizes a fine-to-coarse process in which local support is accumulated. The algorithm is concise, efficient, and above all, gives good results for complex scenes.
This paper deals with the development of an efficient model based approach to detect and characterize precisely important features such as edges, corners and vertices. The key of our approach is first to propose some ...
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ISBN:
(纸本)081863880X
This paper deals with the development of an efficient model based approach to detect and characterize precisely important features such as edges, corners and vertices. The key of our approach is first to propose some efficient models associated to each of these features and second, to efficiently extract and characterize these features directly from the image by searching the parameters of the model that best approximate the observed grey level image intensities. Due to the large amount of time required by a first approach that assumes the blur of the imaging acquisition system to be describable by a 2D Gaussian filter, different solutions that drastically reduce this computational time are considered and developed in this paper. The important problem of the initialization phase in the minimization process is also considered and an original and efficient solution is proposed. A large number of experiments involving real images have been carried out in order to test and compare the reliability, the robustness and the efficiency of the different proposed approaches.
The use of higher level patternrecognition for 3-D reconstruction of objects from multiple 2-D images can be computationally very intensive. In our applications, we needed to process data sets consisting of up to 150...
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ISBN:
(纸本)0780307852
The use of higher level patternrecognition for 3-D reconstruction of objects from multiple 2-D images can be computationally very intensive. In our applications, we needed to process data sets consisting of up to 150 cross-sectional images and automatically reconstruct the surfaces describing the object. On a Silicon Graphics Indigo workstation, such a task normally takes one hour. By splitting up the reconstruction among many such machines using high level Unix calls, the job can be handled effectively with a corresponding decrease in reconstruction time, without significantly affecting the performance of any one machine.
The main contributions of this research are: (1) the derivation of the probability density function (pdf) of disparity changes in stereo matching based on the pdf of depth changes in the world and on the parameters of...
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ISBN:
(纸本)0818621486
The main contributions of this research are: (1) the derivation of the probability density function (pdf) of disparity changes in stereo matching based on the pdf of depth changes in the world and on the parameters of the stereo image formation process, (2) the definition of a match support equation based on the derived pdf, and (3) the incorporation of the support equation into a relaxation matching algorithm. The derived pdf and support equation are applicable to many existing stereo algorithms.
The extension of the iterated function system (IFS) theory dealing with probability functions instead of numbers is applied to texture analysis. The results allow encoding and reconstruction of textured images, and he...
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ISBN:
(纸本)0818621486
The extension of the iterated function system (IFS) theory dealing with probability functions instead of numbers is applied to texture analysis. The results allow encoding and reconstruction of textured images, and hence the compression of data to tackle the problem of texture segmentation in a rigorous manner.
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