Proceedings ArticleDOI
A parallel algorithm for 3D point pattern matching
Krishnendu Chaudhury,Rajiv Mehrotra,N. Ranganathan +2 more
- pp 105-110
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TLDR
The authors present a parallel algorithm for determining the correspondence between two sets of three-dimensional (3D) object feature points, referred to as frame 1 and frame 2, respectively, that is adaptive, i.e. it works with a variable number of processors and uses a relatively weaker model of parallel computation.Abstract:
The authors present a parallel algorithm for determining the correspondence between two sets of three-dimensional (3D) object feature points, referred to as frame 1 and frame 2, respectively. The points in frame 1 and frame 2 are obtained by observing the same dynamic scene (with multiple rigid objects), at two different instants of time. The parallel algorithm presented is adaptive, i.e. it works with a variable number of processors, and it uses a relatively weaker (and cheaper) model of parallel computation, namely, single-instruction multiple-data (SIMD) with shared memory blocks. The algorithm segments the scene based on difference in motion parameters. The approach is robust in the sense that it does not require the number of points in frame 1 and frame 2 to be identical. >read more
Citations
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Proceedings ArticleDOI
A microeconomic model for simultaneous gate sizing and voltage scaling for power optimization
TL;DR: The main contribution of this work is the application of microeconomic models and game theory for these VLSI CAD problems and the proposed solutions yield better power optimization than other methods as shown in the experimental results for MCNC '91 benchmark circuits.
References
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Journal ArticleDOI
Determining optical flow
TL;DR: In this paper, a method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image, and an iterative implementation is shown which successfully computes the Optical Flow for a number of synthetic image sequences.
Proceedings ArticleDOI
Determining Optical Flow
TL;DR: In this article, a method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image, and an iterative implementation is shown which successfully computes the Optical Flow for a number of synthetic image sequences.
Journal ArticleDOI
The representation, recognition, and locating of 3-d objects
Olivier Faugeras,Martial Hebert +1 more
TL;DR: This work proposes the paradigm of recognizing objects while locating them as a prediction and verifi cation scheme that makes efficient use of the shape representation and the matching algorithm, which are general and can be used for other types of data, such as ultrasound, stereo, and tactile.
Journal ArticleDOI
On the computation of motion from sequences of images-A review
TL;DR: Two distinct paradigms are highlighted: (i) the feature- based approach and (ii) the optical-flow-based approach: the comparative merits/demerits of these approaches are discussed.
Journal ArticleDOI
Model-based recognition and localization from sparse range or tactile data
TL;DR: In this paper, the authors show that inconsistent hypotheses about pairings between sensed points and object surfaces can be discarded efficiently by using local constraints on distances between faces, angles between face normals, and angles (relative to the surface normals) of vectors between the sensed points.