Abstract
Fingerprinting is the process of mapping content or fragments of it, into unique, discriminative hashes called fingerprints. In this paper, we propose an automated video identification algorithm that employs fingerprinting for storing videos inside its database. When queried using a degraded short video segment, the objective of the system is to retrieve the original video to which it corresponds to, both accurately and in real-time. We present an algorithm that first, extracts key frames for temporal alignment of the query and its actual database video, and then computes spatio-temporal fingerprints locally within such frames, to indicate a content-match. All stages of the algorithm have been shown to be highly stable and reproducible even when strong distortions are applied to the query.
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References
Oostveen, J., Kalker, T., Haitsma, J.: Feature extraction and a database strategy for video fingerprinting. In: International conference on recent advances in visual information systems, pp. 117–128 (2002)
Hampapur, A., Bolle, R.: Videogrep: video copy detection using inverted file indices. Technical report, IBM research (2001)
Hua, X.-S., Chen, X., Zhang, H.-J.: Robust video signature based on ordinal measure. ICIP 1, 685–688 (2004)
Lee, S., Yoo, C.-D.: Video fingerprinting based on centroids of gradient distortions. In: ICASSP, pp. 401–404 (2006)
Sivic, J., Zisserman, A.: Video google: A text retrieval approach to object matching in videos. ICCV 2, 1–8 (2003)
Matas, J., Chum, O., Martin, U., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. BMVC 1, 384–393 (2002)
Nistér, D., Stewénius, H.: Scalable recognition with a vocabulary tree. CVPR 2, 2161–2168 (2006)
Massoudi, A., Lefebvre, F., Demarty, C.-H., Oisel, L., Chupeau, B.: A video fingerprint based on visual digest and local fingerprints. ICIP, 2297–2300 (2006)
Donser, M., Bischof, H.: 3D segmentation by maximally stable volumes (MSVs). ICPR, 63–66 (2006)
Lowe, D.: Distinctive image features from scale-invariant keypoints. IJCV 60(2), 91–110 (2004)
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© 2007 Springer-Verlag Berlin Heidelberg
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Singh, G., Puri, M., Lubin, J., Sawhney, H. (2007). Content-Based Matching of Videos Using Local Spatio-temporal Fingerprints. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4844. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76390-1_41
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DOI: https://doi.org/10.1007/978-3-540-76390-1_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76389-5
Online ISBN: 978-3-540-76390-1
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