A Hybrid System for Affine-invariant Trajectory Retrieval. Bashir, F., Khokhar, A., & Schonfeld, D. In Proceedings of the ACM SIGMM International Workshop on Multimedia Information Retrieval, pages 235--242, 2004. ![A Hybrid System for Affine-invariant Trajectory Retrieval [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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
@InProceedings{Bashir2004,
Title = {A Hybrid System for Affine-invariant Trajectory Retrieval},
Author = {Bashir, F. and Khokhar, A. and Schonfeld, D.},
Booktitle = {Proceedings of the ACM SIGMM International Workshop on Multimedia Information Retrieval},
Year = {2004},
Pages = {235--242},
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},
Acmid = {1026750},
Doi = {10.1145/1026711.1026750},
ISBN = {1-58113-940-3},
Keywords = {affine-invariant trajectory descriptors, curvature scale space, fourier descriptor, motion based indexing and retrieval, principal component analysis},
Location = {New York, NY, USA},
Numpages = {8},
Timestamp = {2014.12.11},
Url = {http://doi.acm.org/10.1145/1026711.1026750}
}
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