Ruxandra Tapu

TL;DR: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative; results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years.

TL;DR: A real-time obstacle detection and classification system designed to assist visually impaired people to navigate safely, in indoor and outdoor environments, by handling a smartphone device and incorporates HOG descriptor into the Bag of Visual Words (BoVW) retrieval framework and demonstrates how this combination may be used for obstacle classification in video streams.

TL;DR: A survey of wearable/assistive devices and provides a critical presentation of each system, while emphasizing related strengths and limitations, to inform the research community and the VI people about the capabilities of existing systems, the progress in assistive technologies and provide a glimpse in the possible short/medium term axes of research that can improve existing devices.

TL;DR: A novel wearable assistive device designed to facilitate the autonomous navigation of blind and VI people in highly dynamic urban scenes that makes it possible to identify accurately both static and highly dynamic objects existent in a scene, regardless on their location, size or shape.

TL;DR: The DEEP-SEE framework is integrated into a novel assistive device, designed to improve cognition of VI people and to increase their safety when navigating in crowded urban scenes, which shows high accuracy and robustness scores regardless on the scene dynamics.