Computer Vision (CV) research focuses on analyzing and understanding visual data in order to extract meaningful information contained within still images and video streams. Example outputs of computer vision algorithms include detected object locations and labels (such as faces, cars, pedestrians), a 3D model of the scene generated from images, images containing virtual objects rendered from the camera point-of-view, and pixel-level segmentation of the objects.
Our research concentrates on following topics.
- Computer Vision Research Group (CVRG), directed by Assist. Prof. Yalın Baştanlar
- 3D Reconstruction from Images
- Visual Object Detection/Classification
- Omnidirectional Vision
- Vision for Traffic Analysis
- Visual Intelligence Research Group (VIRG), directed by Assist. Prof. Mustafa Özuysal
- Real-time Object Detection and Tracking
- Large Scale Object Identification
- Augmented Reality
- Scene Text Recognition