A hybrid system for affine-invariant trajectory retrieval

Authors:
Faisal Bashir;Ashfaq Khokhar;Dan Schonfeld
Affiliations:
University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL
Venue:
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Year:
2004

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Abstract

This paper studies efficient feature spaces for content based indexing and retrieval of object motion trajectories. Taking object trajectory data as input, we first investigate highly compact affine invariant feature spaces based on Fourier Descriptors (FD) and Principal Component Analysis (PCA) techniques. Based on these feature spaces, we then develop a hybrid content based indexing and retrieval system that employs a two-stage matching scheme. The first stage uses affine-invariant Fourier Descriptor (FD) for indexing and retrieval. Top few results from this stage along with the original query are then posed to the second stage of the matching system that employs Principal Component Analysis (PCA) for fast retrieval. We compare our system's performance with two other approaches borrowed from 2-D shape representation in image analysis. For quantitative analysis of the system performance, we report query results in terms of precision-recall metrics