Book ChapterDOI
The Infection Algorithm: An Artificial Epidemic Approach for Dense Stereo Matching
Gustavo Olague,Francisco Vega,Cynthia B. Perez,Evelyne Lutton +3 more
- pp 622-632
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TLDR
In this article, a bio-inspired approach applied to a problem of stereo images matching is presented, which is based on an artifical epidemic process, that is called "the infection algorithm".Abstract:
We present a new bio-inspired approach applied to a problem of stereo images matching. This approach is based on an artifical epidemic process, that we call “the infection algorithm.” The problem at hand is a basic one in computer vision for 3D scene reconstruction. It has many complex aspects and is known as an extremely difficult one. The aim is to match the contents of two images in order to obtain 3D informations which allow the generation of simulated projections from a viewpoint that is different from the ones of the initial photographs. This process is known as view synthesis. The algorithm we propose exploits the image contents in order to only produce the necessary 3D depth information, while saving computational time. It is based on a set of distributed rules, that propagate like an artificial epidemy over the images. Experiments on a pair of real images are presented, and realistic reprojected images have been generated.read more
Citations
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Journal ArticleDOI
Review of stereo vision algorithms and their suitability for resource-limited systems
TL;DR: This work provides a comprehensive review of stereo vision algorithms with specific emphasis on real-time performance to identify those suitable for resource-limited systems and to encourage further research and development of the same.
Book ChapterDOI
The honeybee search algorithm for three-dimensional reconstruction
Gustavo Olague,Cesar Puente +1 more
TL;DR: This paper investigates the communication system of honeybees with the purpose of obtaining an intelligent approach for three-dimensional reconstruction and proposes a new framework in which the 3D points communicate between them to achieve an improved sparse reconstruction.
Journal ArticleDOI
The Infection Algorithm: An Artificial Epidemic Approach for Dense Stereo Correspondence
TL;DR: This work presents a new bio-inspired approach applied to a problem of stereo image matching based on an artificial epidemic process, which it is called the infection algorithm, based on a set of distributed rules.
Proceedings ArticleDOI
Parisian evolution with honeybees for three-dimensional reconstruction
Gustavo Olague,Cesar Puente +1 more
TL;DR: A novel analogy with the way in which honeybee colonies operate is introduced in order to solve the problem of sparse and quasi dense reconstruction and a new adaptive behavior strategy is presented based on the "divide and conquer" approach used by the honeybee colony to solve search problems.
Proceedings ArticleDOI
An independent and non-intrusive laser pointer environment control device system
TL;DR: A system is developed that is able to recognize and act on the device that the handicapped person wants to use and is controlled by means of a domotic system, using KNX architecture.
References
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TL;DR: In this article, the authors considered the problem of finding a causal factor which appears to be adequate to account for the magnitude of the frequent epidemics of disease which visit almost every population.
A Contribution to the Mathematical Theory of Epidemics.
TL;DR: The present communication discussion will be limited to the case in which all members of the community are initially equally susceptible to the disease, and it will be further assumed that complete immunity is conferred by a single infection.
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Advances in computational stereo
TL;DR: This work reviews recent advances in computational stereo, focusing primarily on three important topics: correspondence methods, methods for occlusion, and real-time implementations.
Journal ArticleDOI
Stereo matching using belief propagation
TL;DR: This paper formulate the stereo matching problem as a Markov network and solve it using Bayesian belief propagation to obtain the maximum a posteriori (MAP) estimation in the Markovnetwork.
Book ChapterDOI
Stereo Matching Using Belief Propagation
TL;DR: This paper forms the stereo matching problem as a Markov network consisting of three coupled Markov random fields, and obtains the maximum a posteriori (MAP) estimation in the Markovnetwork by applying a Bayesian belief propagation (BP) algorithm.