Marker-based augmented reality (AR) is extremely popular nowadays. However, full user immersion is possible only in the case of robust real-time computer vision solutions working on the mobile device. We have developed a custom hybrid tracking system based on local feature tracking and template-based matching.
Object recognition is an important computer vision and machine learning problem. A particular case is automatic target recognition (ATR) on radar images. In the project, our team has developed a custom classification algorithm based on two different tools. We have been working with MSTAR dataset.
Systems for detection and tracking of moving objects have a high demand nowadays. Our purpose was to develop the system for the analysis of the humans’ activity in the supermarket. In particular, to cluster the regions of interest (ROI), to detect, track and count the people.