| Autor: |
Paula Niels Spinoza, Jean-Pierre Jessel, Andriamasinoro Rahajaniaina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Advances in Computer Vision and Computational Biology ISBN: 9783030710507 |
| Popis: |
In this chapter, we propose an optimization of the a-contrario clustering method using the probabilistic Guillaume Khenchaff Measure (MGK) quality technique. A-contrario is used for tracking salient objects in the scene in real time. This method analyzes the data contained in a motion vector, which contains the scattered optical flow accumulated points of interest. The aim of our study is to improve the first results obtained from the Number of False Alarm (NFA) criterion by using MGK to bring together the group of points endowed with a coherent movement of the binary tree. The idea is to isolate dynamic points so that we can use static points in the future. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
