Shape modeling from multiple view images using GAs

Kirihara, Satoshi; Saitō, Hideo

doi:10.1007/3-540-63931-4_248

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…One example is a 3D shape recovery of a compact object from a set of its shadows [4,5] or from a set of its pictures [6,7,8], or still from a set of its X-ray radiographic data at different view angles.…”

Section: D Image Recovery From a Set Of 2d Datamentioning

confidence: 99%

A Bayesian Approach for Data and Image Fusion

Mohammad‐Djafari¹

2003

AIP Conference Proceedings

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Abstract. This paper is a tutorial on Bayesian estimation approach to multi-sensor data and image fusion. First a few examples of simple image fusion problems are presented. Then, the simple case of registered image fusion problem is considered to show the basics of the Bayesian estimation approach and its link to classical data fusion methods such as simple mean or median values, Principal Component Analysis (PCA), Factor Analysis (FA) and Independent Component Analysis (ICA). Then, the case of simultaneous registration and fusion of images is considered. Finally, the problem of fusion of really heterogeneous data such as X-ray radiographic and ultrasound echographic data for computed tomography image reconstruction of 2D or 3D objects are considered. For each of the mentioned data fusion problems, a basic method is presented and illustrated through some simulation results.

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Section: D Image Recovery From a Set Of 2d Datamentioning

confidence: 99%

A Bayesian Approach for Data and Image Fusion

Mohammad‐Djafari¹

2003

AIP Conference Proceedings

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“…Thus, superior GAs with a capability for searching over a wide area are used as the search scheme. The GA is a probabilistic search scheme simulating biological evolution, and schemes associated with stereo vision [14,15] have been proposed.…”

Section: Search For Surface Model By Gamentioning

confidence: 99%

A proposal for extracting an object's surface from stereo degree‐of‐correspondence space considering occlusions

Katayama

Okutomi

2001

Electron Comm Jpn Pt II

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SUMMARYThe ambiguity of correspondence assignment is alleviated by utilizing the state of the neighboring correspondence of the focal point (local support) in detecting the points of correspondence in stereo vision. However, in detecting the area base points of correspondence with evaluations of the correspondence using windows, specific local supports are utilized, which can interfere with the correct correspondence assignments. In this paper, a scheme for performing correspondence assignments considering local supports which coincide correctly with the surface of an object is proposed. In this scheme, the surface of the object is directly detected as a surface model, using a new proposed GA detection scheme from the stereo degree-of-correspondence space in which the degree of correspondence is expressed as three-dimensional data. As a result, correspondence assignment is performed with correct local supports by evaluating various surface models obtained by GA search from the stereo degree-of-correspondence space. In addition, the areas in which occlusions have occurred are specified by considering uniformity requirements in searching for surface models. Thus, a method for improving the areas containing occlusions utilizing multiple-camera stereo vision is proposed. In this paper, the construction of the stereo degree-of-correspondence space, the GA search scheme, and the specification and improvement of occlusions are presented and the results of simulation experiments with objects of simple shapes are presented. © 2001 Scripta Technica, Electron Comm Jpn Pt 2, 84(8): 3848, 2001

show abstract

Shape modeling from multiple view images using GAs

Cited by 2 publications

References 8 publications

A Bayesian Approach for Data and Image Fusion

A Bayesian Approach for Data and Image Fusion

A proposal for extracting an object's surface from stereo degree‐of‐correspondence space considering occlusions

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