In this paper we present a statistical method for estimating the relative geometry between two images and give useful methods to characterise motion estimation error. We argue that the estimation of the camera motion should be done in a statistical framework and describe a solution for the case of calibrated images. Statistical bootstrap is used to compute the underlying probability structure o...

Accurate software development effort estimation is a critical part of software projects. Effective development of software is based on accurate effort estimation. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software development effort prediction is still a challenging endeavor in the field of software engineering, especially in ...

Regression analysis is an area of statistics that deals with the investigation of the dependence of a variable upon one or more variables. Recently, much research has studied fuzzy estimation. There are some approaches existing in the literature for the estimation of the fuzzy regression model. Two of them are frequently used in parameter estimation, one of which is proposed by Tanaka et al [21...

Quantitative measurements of tumor in general and tumor volume in particular, become more realistic with the use of Magnetic Resonance imaging, especially when the tumor morphological changes become irregular and difficult to assess by clinical examination. However, tumor volume estimation strongly depends on the image segmentation, which is fuzzy by nature. In this paper a fuzzy approach is pr...

This paper studies traffic variable estimation, and presents a method of estimation for the number of vehicle waiting for queue (NVWQ) based on neuro-fuzzy at urban intersection. we present results of training the neural network for a detectorized intersection in Changsha City. The accuracy of NVWQ estimation using the fuzzy neural networks approaches is more than 90%. The fuzzy neural networks...

In this chapter, global motion estimation and its applications are given. Firstly we give the definitions of global motion and global motion estimation. Secondly, the parametric representations of global motion models are provided. Thirdly, global estimation approaches including pixel domain based global motion estimation, hierarchical global motion estimation, partial pixel set based global mo...

Pose estimation involves reconstructing the configuration of a moving body from images sequences. In this paper we present a general framework for pose estimation of unknown objects based on Shafer’s evidential reasoning. During learning an evidential model of the object is built, integrating different image features to improve both estimation robustness and precision. All the measurements comi...

Digital video stabilization approaches typically degrade their performances in presence of periodic patterns. Any kind of matching between consecutive frames is not usually able to work in presence of these kind of signals: the motion estimation engine is deceived and its performances degrade abruptly. In this paper we propose a fast fuzzy classifier able to recognize periodic and aperiodic pat...

In this work, the Parameters Estimation in petroleum wells is presented; it is based on Intelligent Systems (neural networks and fuzzy logic). For validating the results, the estimation is applied in wells that need artificial lift using well heading data (gas and production pressure). Key-Words: neo-fuzzy models, oil system production, artificial gas lift wells, parameters estimation.