Time-Series Linear Search for Video Copies Based on Compact Signature Manipulation and Containment Relation Modeling

• Published in: IEEE transactions on circuits and systems for video technology Vol. 20; no. 11; pp. 1603 - 1613
• Main Authors: CHIU, Chih-Yi, WANG, Hsin-Min
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Applied sciences; Complexity theory; Containment; Content-based retrieval; Cryptography; Editing; Exact sciences and technology; fingerprint identification; Histograms; Indexing; Information theory; Information, signal and communications theory; Manipulation; Mathematical models; near-duplicate; Pattern recognition; Robustness; Searching; Signal and communications theory; Signal processing; Signatures; Studies; Telecommunications and information theory; Transformations; video copy detection; Video sequences; Visualization; Biometrics; Content based retrieval; Image recognition; Query; Video signal; Time series; near-duplicate; Information retrieval; Compact design; Pattern recognition; Modeling; Copy protection; Search algorithm; Fingerprint identification; Information protection; Image sequence; Content-based retrieval; Robustness; Automatic recognition; video copy detection
• ISSN: 1051-8215; 1558-2205
• DOI: 10.1109/TCSVT.2010.2087471

This paper presents a novel time-series linear search (TLS) method for detecting video copies. The method utilizes a sliding window to locate window sequences that are near-duplicates of a given query sequence. We address two issues of the conventional TLS method in order to strengthen its video copy detection capability. First, to accelerate the TLS process, we use a sequence-level signature as a compact representation of a video sequence based on the min-hash theory, and develop an efficient heap manipulation technique for fast generation of each window sequence's signature. Second, to improve the robustness of the TLS method, we use two techniques, namely, window length estimation and threshold transform, to resolve the containment relation problem caused by various types of video transformation and editing, such as frame cropping and speed change. The results of experiments on the MUSCLE-VCD-2007 dataset demonstrate that the proposed method is efficient and robust against different types of video transformation and editing.