Share
detection of moving objects by spatio-temporal motion analysis
Rabe Clemens
(Author)
·
Sudwestdeutscher Verlag Fur Hochschulschrifte
· Paperback
detection of moving objects by spatio-temporal motion analysis - Rabe Clemens
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: Spain
(Import costs included in the price)
It will be shipped from our warehouse between
Thursday, June 27 and
Monday, July 08.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "detection of moving objects by spatio-temporal motion analysis"
Driver assistance systems of the future require a thorough understanding of the car's environment. In this thesis, a novel principle (6D-Vision) is presented and investigated in detail, which allows the reconstruction of the 3D motion field from the image sequence obtained by a stereo camera system. Given correspondences of stereo measurements over time, this principle estimates the 3D position and the 3D motion vector of selected points using Kalman Filters, resulting in a real-time estimation of the observed motion field. To estimate the absolute motion field, the ego-motion of the moving observer must be known precisely. Thus, a novel algorithm to estimate the ego-motion from the image sequence is presented. As the 6D-Vision principle is not restricted to particular image processing algorithms, various optical flow and stereo algorithms are evaluated. In addition, two novel scene flow algorithms are introduced, measuring the optical flow and stereo information in a combined approach. This yields more precise and robust results. The application to real-world data, including a demonstrator vehicle for autonomous collision avoidance, is illustrated throughout the thesis.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.
