Flux optique
Flux optique is a concept in vision par ordinateur and traitement d'image that refers to the pattern of motion of objects as perceived through a sequence of images. It is derived from the movement of objects between two or more frames captured by a camera. By analyzing these changes, algorithms can estimate the velocity of objects, their direction, and even depth perception.
Le flux optique repose sur le principe que le mouvement apparent des objets résulte à la fois du mouvement de l'observateur (caméra) et du mouvement des objets dans la scène. Le déplacement est généralement représenté sous forme de champ de vecteurs, où chaque vecteur correspond au mouvement d'un pixel d'objet d'une image à l'autre.
Il existe deux principales approches pour calculer le flux optique : flux optique dense and flux optique sparse. Dense optical flow calculates motion vectors for every pixel in the image, providing a comprehensive view of all object movements. In contrast, sparse optical flow focuses on specific feature points, tracking their motion across frames. Both methods have their unique applications and advantages.
Optical flow is widely used in various applications including video surveillance, autonomous driving, motion analysis, and réalité augmentée. It helps systems understand dynamic environments by interpreting how objects move relative to each other and the observer. Furthermore, it plays a crucial role in the development of algorithms for object tracking, scene reconstruction, and motion-based segmentation.