Content-Based Matching of Videos Using Local Spatio-temporal Fingerprints
| Autor: | Gajinder Singh, Jeffrey Lubin, Manika Puri, Harpreet Sawhney |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Matching (graph theory)
business.industry Computer science Hash function ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Identification (information) Discriminative model Video tracking Content (measure theory) Key (cryptography) Computer vision Artificial intelligence business |
| Zdroj: | Computer Vision – ACCV 2007 ISBN: 9783540763895 ACCV (2) |
| DOI: | 10.1007/978-3-540-76390-1_41 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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