Grupo de Tratamiento de Imágenes



News and Events 

Cátedra Ingeniero General D. Antonio Remón y Zarco del Valle

On November 25th, Daniel Fuertes, a PhD student at GTI, recieved the Cátedra Ingeniero General D. Antonio Remón y Zarco del Valle award for the work entitled "People detection with omnidirectional cameras using a spatial grid of deep learning classifiers".




Abstract: novel deep-learning people detection algorithm using omnidirectional cameras is presented, which only requires point-based annotations, unlike most of the prominent works that require bounding box annotations. Thus, the effort of manually annotating the needed training databases is significantly reduced, allowing a faster system deployment. The algorithm is based on a novel deep neural network architecture that implements the concept of Grid of Spatial-Aware Classifiers, but allowing end-to-end training that improves the performance of the whole system. The designed algorithm satisfactorily handles the severe geometric distortions of the omnidirectional images, which typically degrades the performance of state-of-the-art detectors, without requiring any camera calibration. The algorithm has been evaluated in well-known omnidirectional image databases (PIROPO, BOMNI, and MW-18Mar) and compared with several works of the state of the art. More info