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Image Processing to Detect and Classify Situations and States of Elderly People

  • Ramón Reig-Bolaño
  • Pere Marti-Puig
  • Javier Bajo
  • Sara Rodríguez
  • Juan F. De Paz
  • Manuel P. Rubio
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 87)

Abstract

Monitoring and tracking of elderly people using vision algorithms is an strategy gaining relevance to detect anomalous and potentially dangerous situations and react immediately. In general vision algorithms for monitoring and tracking are very costly and take a lot of time to respond, which is highly inconvenient since many applications can require action to be taken in real time. A multi-agent system (MAS) can establish a social model to automate the tasks carried out by the human experts during the process of analyzing images obtained by cameras. This study presents a detector agent integrated in a MAS that can process stereoscopic images to detect and classify situations and states of elderly people in geriatric residences by combining a series of novel techniques. We will talk in details about the combination of techniques used to perform the detection process, subdivided into human detection, human tracking ,and human behavior understanding, and where there is a case-based reasoning (CBR) model that allows the system to add reasoning capabilities.

Keywords

Multi-Agent Systems stereo processing human detection Case Based Reasoning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ramón Reig-Bolaño
    • 1
  • Pere Marti-Puig
    • 1
  • Javier Bajo
    • 2
  • Sara Rodríguez
    • 2
  • Juan F. De Paz
    • 2
  • Manuel P. Rubio
    • 2
  1. 1.Department of Digital and Information TechnologiesUniversity of VicBarcelonaSpain
  2. 2.Department of Computer ScienceUniversity of SalamancaSalamancaSpain

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