ESR7: UGENT

Cooperative tracking and visual analytics

@ Dep. Telecommunications and Information Processing (Ghent University), Belgium

One of the most common but still challenging requirements in multi-camera video processing is the ability to automatically track objects over multiple cameras. In intelligent traffic management, for example, objects of interest include not only vehicles but also weak road users. Current state of the art approaches focus either on feature-modelling that designs descriptors invariant to camera changes or on metric learning that often require prohibitive amount of training data. Vehicle tracking/re-identification is equally challenging in difficult circumstances. The first goal of this project is to design algorithms for distributed multiple targets tracking through a decentralized approach. The second goal is to improve object detection and tracking using a multi-sensor approach. Thermal cameras have promising potential in surveillance applications, especially when combined with optical cameras. The third goal of the project is to provide solutions for behaviour analysis and action recognition. The research will use high-level analysis to automatically determine which cameras observe the same or similar action, such as pedestrians waiting to cross the street. Deep learning is a promising approach.