Skip to Main content Skip to Navigation

Détection d’objets en mouvement à l’aide d’une caméra mobile

Abstract : Moving objects detection in video streams is a commonly used technique in many computer vision algorithms. The detection becomes more complex when the camera is moving. The environment observed by this type of camera appeared moving and it is more difficult to distinguish the objects which are in movement from the others that composed the static part of the scene. In this thesis we propose contributions for the detection of moving objects in the video stream of a moving camera. The main idea to differenciate between moving and static objects based on 3D distances. 3D positions of feature points extracted from images are estimated by triangulation and then their 3D motions are analyzed in order to provide a sparse static/moving labeling. To provide a more robust detection, the analysis of the 3D motions is compared to those of feature points previously estimated static. A confidance value updated over time is used to decide on labels to attribute to each point.We make experiments on virtual (from the Previz project 1) and real datasets (known by the community [Och+14]) and we compare the results with the state of the art. The results show that our 3D constraint coupled with a statistical and temporal analysis of motions allow to detect moving elements in the video stream of a moving camera even in complex cases where apparent motions of the scene are not similars
Complete list of metadata

Cited literature [83 references]  Display  Hide  Download
Contributor : Abes Star :  Contact
Submitted on : Thursday, May 3, 2018 - 3:22:06 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:10 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 1:01:09 PM


Version validated by the jury (STAR)


  • HAL Id : tel-01784521, version 1


Marie-Neige Chapel. Détection d’objets en mouvement à l’aide d’une caméra mobile. Vision par ordinateur et reconnaissance de formes [cs.CV]. Université de Lyon, 2017. Français. ⟨NNT : 2017LYSE1156⟩. ⟨tel-01784521⟩



Record views


Files downloads