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In this work, we propose a fast content-based video querying system forlarge-scale video search. The proposed system is distinguished from similarworks with two major contributions. First contribution is superiority of jointusage of repeated content representation and efficient hashing mechanisms.Repeated content representation is utilized with a simple yet robust feature,which is based on edge energy of frames. Each of the representation isconverted into hash code with Hamming Embedding method for further queries.Second contribution is novel queue-based voting scheme that leads to modestmemory requirements with gradual memory allocation capability, contrary tocomplete brute-force temporal voting schemes. This aspect enables us to makequeries on large video databases conveniently, even on commodity computers withlimited memory capacity. Our results show that the system can respond to videoqueries on a large video database with fast query times, high recall rate andvery low memory and disk requirements.

Large-Scale Video Search with Efficient Temporal Voting Structure