HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal…

• NU
  National University of Singapore
• AN
  Agence Nationale de la Recherche
• L
  Labex

  Award: ANR-10-LABX-65
• SF
  Seventh Framework Programme

  Awards: 604102 (HBP), FP7/2007-2013