Title :
Syntactic Matching of Trajectories for Ambient Intelligence Applications
Author :
Piotto, Nicola ; Conci, Nicola ; De Natale, Francesco G B
Author_Institution :
Dept. of Eng. & Comput. Sci., Univ. of Trento, Trento, Italy
Abstract :
In this paper we propose a novel approach for syntactic description and matching of object trajectories in digital video, suitable for classification and recognition purposes. Trajectories are first segmented by detecting the meaningful discontinuities in time and space, and are successively expressed through an ad-hoc syntax. A suitable metric is then proposed, which allows determining the similarity among trajectories, based on the so-called inexact or approximate matching. The metric mimics the algorithms used in bio-informatics to match DNA sequences, and returns a score, which allows identifying the analogies among different trajectories on both global and local basis. The tool can therefore be adopted for the analysis, classification, and learning of motion patterns, in activity detection or behavioral understanding.
Keywords :
image classification; image matching; image motion analysis; image segmentation; learning (artificial intelligence); video signal processing; DNA sequence matching; activity detection; ambient intelligence; approximate matching; behavioral understanding; bioinformatics; digital video; image classification; image recognition; image segmentation; inexact matching; motion pattern learning; object trajectory; syntactic description; syntactic matching; Ambient intelligence; trajectory analysis; trajectory matching; trajectory representation; visual surveillance;
Journal_Title :
Multimedia, IEEE Transactions on
DOI :
10.1109/TMM.2009.2030746