Detection of cyclic human activities based on the morphological analysis of the inter-frame similarity matrix

  • Authors:

  • Alexandra Branzan Albu;Mehran Yazdi;Robert Bergevin

  • Affiliations:

  • Computer Vision and Systems Laboratory, Department of ECE, Laval University, Québec, Canada, G1K 7P4;Computer Vision and Systems Laboratory, Department of ECE, Laval University, Québec, Canada, G1K 7P4;Computer Vision and Systems Laboratory, Department of ECE, Laval University, Québec, Canada, G1K 7P4

  • Venue:
  • Real-Time Imaging
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes a new method for the temporal segmentation of periodic human activities from continuous real-world indoor video sequences acquired with a static camera. The proposed approach is based on the concept of inter-frame similarity matrix. Indeed, this matrix contains relevant information for the analysis of cyclic and symmetric human activities, where the motion performed during the first semi-cycle is repeated in the opposite direction during the second semi-cycle. Thus, the pattern associated with a periodic activity in the similarity matrix is rectangular and decomposable into elementary units. We propose a morphology-based approach for the detection and analysis of activity patterns. Pattern extraction is further used for the detection of the temporal boundaries of the cyclic symmetric activities. The approach for experimental evaluation is based on a statistical estimation of the ground truth segmentation and on a confidence ratio for temporal segmentations.