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- Maurício Marengoni, Bruce A. Draper, Allen R. Hanson, R. Sitaraman
- Image Vision Comput.
- 2000

The Art Gallery Problem deals with determining the number of observers necessary to cover an art gallery room such that every point is seen by at least one observer. This problem is well known and has a linear time solution for the 2 dimensional case, but little is known in the 3-D case. In this paper we present a polynomial time solution for the 3-D… (More)

The Art Gallery Problem is the problem of determining the number of observers necessary to cover an art gallery room such that every point is seen by at least one observer. This problem is well known and has a linear solution for the 2 dimensional case, but little is known in the 3-D case. In this paper we present a polynomial time solution for the 3-D… (More)

One important task in image interpretation is the process of understanding and identifying segments of an image. Ascender II is a knowledge-based vision system in which the selection of IU algorithms and the fusion of information provided by them is combined in an efficient way. A major problem with many knowledge-based systems is that the knowledge base,… (More)

- Maurício Marengoni, Denise Stringhini
- SIBGRAPI Tutorials
- 2011

This paper presents some more advanced topics in image processing and computer vision, such as Principal Components Analysis, Matching Techniques, Machine Learning Techniques, Tracking and Optical Flow and Parallel Computer Vision using CUDA. These concepts will be presented using the openCV library, which is a free computer vision library for C/C++… (More)

- Luiz Carlos Rodrigues, Maurício Marengoni
- VISAPP
- 2015

- Maurício Marengoni, Allen R. Hanson, Shlomo Zilberstein, Edward M. Riseman
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2003

This paper presents a control structure for a general-purpose image understanding system. It addresses the high level of uncertainty in local hypotheses and the computational complexity of image interpretation. The control of vision algorithms is done by an independent subsystem that uses Bayesian networks and utility theory to compute marginal value of… (More)

Image understanding (IU) techniques for automatic site reconstruction have demonstrated success within restricted domains and for small numbers of model classes. However, these techniques often fail when applied out of context and do not \scale-up" into a more general solution. Under the APGD program, we are constructing a knowledge-based site… (More)

This paper presents interim results from an ongoing project on aerial image reconstruction. One important task in image interpretation is the process of understanding and identifying segments of an image. In this eeort a knowledge based vision system is being presented, where the selection of IU algorithms and the fusion of information provided by them is… (More)

- Guilherme Bittencourt, Maurício Marengoni, Sandra A. Sandri
- ECSQARU
- 1993

This paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complexity of image interpretation. The control of vision algorithms is performed by an independent subsystem that uses Bayesian networks and utility theory to compute the marginal value… (More)