Building visual memories of video streams

A real-time method that automatically creates a visual memory of a scene using the growing neural gas (GNG) algorithm is described. The memory consists of a graph where nodes encode the visual information of a video stream as a limited set of representative images. GNG nodes are automatically generated and dynamically clustered. This method could be employed by robotic platforms in exploratory and rescue missions. © 2012 The Institution of Engineering and Technology

A NOVEL SEGMENTATION METHOD FOR CROWDED SCENES

Video surveillance is one of the most studied application in Computer Vision. We propose a novel method to identify and track people in a complex environment with stereo cameras. It uses two stereo cameras to deal with occlusions, two different background models that handle shadows and illumination changes and a new segmentation algorithm that is effective in crowded environments. The algorithm is able to work in real time and results demonstrating the effectiveness of the approach are shown

A Distributed Gamified System Based on Automatic Assessment of Physical Exercises to Promote Remote Physical Rehabilitation

Physical rehabilitation aims at improving the functional ability and quality of life of patients affected by physical impairments or disabilities. Neurological diseases represent the largest cause of disability worldwide. For many, there is no cure and physiotherapy allows symptoms to be managed. Physiotherapy is based on the daily execution of exercises, traditionally under the supervision of a therapist. However, performing these exercises requires that both the patient and the physiotherapist are together so that the physiotherapist can assist the patient while exercising. For patients with a neurological condition, rehabilitation is a long term process, lasting months or even years. Not withstanding the personal costs, the cost of care/physiotherapy is high and represents €27,711 per year in Spain. This is compounded by a shortage of qualified therapists, often cited as one reason why stroke survivors do not received the recommended amount of therapy. The challenge is even greater in low to mid-income countries where there is a lack of trained personnel as well as under-served and remote regions. Technology can be employed to alleviate these problems by remotely monitoring a rehabilitation session taking place at home or anywhere in the community. This paper presents a computer vision-based system for home-use that automatically assesses how well the patient performs the exercises and transmits the information back to the clinic. The patient and physiotherapist do not need to be co-located. Gamification methods and techniques are used to engage patients when carrying out the rehabilitation routines. To this end, we propose a distributed gamified system that automatically evaluates the performance of exercises by analyzing and comparing motion curves using the DTW (Dynamic Time Warping) algorithm

Smart monitoring of complex public scenes: Collaboration between human guards, security network and robotic platforms

Security operators are increasingly interested in solutions that can provide an automatic understanding of potentially crowded public environments. In this paper, an on-going research is presented, on building a complex system consists of three main components: human security operators carrying sensors, mobile robotic platforms carrying sensors and network of fixed sensors (i.e. cameras) installed in the environment. The main objectives of this research are: 1) to develop models and solutions for an intelligent integration of sensorial information coming from different sources, 2) to develop effective human-robot interaction methods in the paradigm multi-human vs. multi-robot, 3) to integrate all these components in a system that allows for robust and efficient coordination among robots, vision sensors and human guards, in order to enhance surveillance in crowded public environments. Copyright © 2011, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved