Researchers have adapted deep learning techniques in a multi-object tracking framework, overcoming short-term occlusion and achieving remarkable performance without sacrificing computational speed.

Conventional markerless tracking methods struggle with body part misestimations or missing estimates in crowded spaces. In vmTracking, markerless multi-animal tracking is performed on a video ...

Benefiting from the high-speed optoelectronic response and submicrometer positional accuracy of the TD-PSD, the team realized multi-target real-time trajectory tracking with a maximum image output ...

Computer vision has progressed much over the past decade and made its way into all sorts of relevant applications, both in academia and in our daily lives. There are, however, some tasks in this field ...