Optical Flow And Trajectory Estimation Methods
Download Optical Flow And Trajectory Estimation Methods PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Optical Flow And Trajectory Estimation Methods book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Optical Flow and Trajectory Estimation Methods
This brief focuses on two main problems in the domain of optical flow and trajectory estimation: (i) The problem of finding convex optimization methods to apply sparsity to optical flow; and (ii) The problem of how to extend sparsity to improve trajectories in a computationally tractable way. Beginning with a review of optical flow fundamentals, it discusses the commonly used flow estimation strategies and the advantages or shortcomings of each. The brief also introduces the concepts associated with sparsity including dictionaries and low rank matrices. Next, it provides context for optical flow and trajectory methods including algorithms, data sets, and performance measurement. The second half of the brief covers sparse regularization of total variation optical flow and robust low rank trajectories. The authors describe a new approach that uses partially-overlapping patches to accelerate the calculation and is implemented in a coarse-to-fine strategy. Experimental results show that combining total variation and a sparse constraint from a learned dictionary is more effective than employing total variation alone. The brief is targeted at researchers and practitioners in the fields of engineering and computer science. It caters particularly to new researchers looking for cutting edge topics in optical flow as well as veterans of optical flow wishing to learn of the latest advances in multi-frame methods. /div
Imaging Measurement Methods for Flow Analysis
Author: Wolfgang Nitsche
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-04-08
In 2003 the German Research Foundation established a new priority programme on the subject of “Imaging Measurement Methods for Flow Analysis” (SPP 1147). This research programme was based on the fact that experimental ?ow analysis, in addition to theory and numerics, has always played a predominant part both in ?ow research and in other areas of industrial practice. At the time, however, c- parisons with numerical tools (such as Computational Fluid Dynamics), which were increasingly used in research and practical applications, soon made it clear that there are relatively few experimental procedures which can keep up with state-of-the-art numerical methods in respect of their informative value, e.g. with regard to visu- spatial analysis or the dynamics of ?ow ?elds. The priority programme “Imaging Measurement Methods for Flow Analysis” was to help close this development gap. Hence the project was to focus on the investigation of ef?cient measurement me- ods to analyse complex spatial ?ow ?elds. Speci?c cooperations with computer sciences and especially measurement physics were to advance ?ow measurement techniques to a widely renowned key technology, exceeding the classical ?elds of ?uid mechanics by a long chalk.
Computer Vision – ECCV 2024
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation.