Paper
18 May 2006 Model-based recognition using 3D invariants and stereo imaging
Author Affiliations +
Abstract
In this paper, we proposed a three dimensional matching algorithm using geometrical invariants. Invariant relations between 3D objects and 2D images for object recognition has been already developed in Ref. [1]. We proposed a geometrical invariant approach for finding relation between 3D model and stereo image pair. Since the depth information is lost in a single 2D image, we cannot recognize an object perfectly. By constructing a 3D invariant space we can represent a 3D model as a set of points in the invariant space. While matching with the 2D image we can draw a set of invariant light rays in 3D, each ray passing through a 3D invariant model point. If enough rays intersect the model in 3D invariant space we can assume that the model is present in the image. But for a single image the method is not that much reliable as the depth information is never considered. In the proposed method, as the matching is performed using stereo image pair, it is more reliable and accurate.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. T. Rahman and M. S. Alam "Model-based recognition using 3D invariants and stereo imaging", Proc. SPIE 6234, Automatic Target Recognition XVI, 62340D (18 May 2006); https://doi.org/10.1117/12.666284
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KEYWORDS
3D modeling

3D image processing

Cameras

Detection and tracking algorithms

Data modeling

Model-based design

Object recognition

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