Near-Duplicate Web Video Detection
Pp. 26-57 (32)
Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo and Alexander G. Hauptmann
The explosive expansion of the social web makes overwhelming amounts
of web videos available, among which there are a large number of near-duplicate
videos. Current web video search results rely exclusively on text keywords or usersupplied
tags. A search on the keywords of a typical popular video often returns
many duplicate and near-duplicate videos in the top results. Efficient near-duplicate
web video detection is essential for effective search, retrieval, browsing and annotation.
Due to the large variety of near-duplicate web video types ranging from
simple formatting to complex editing, accurate detection generally comes at the
cost of time complexity, particularly for web scale video applications. On the other
hand, timely response to user queries is one important factor that fuels the popularity
of the social web. This chapter will review approaches for near-duplicate
web video detection from different technical viewpoints: combining global features
and local features, integrating content and contextual information, and visual-word based scalable retrieval.
Near-Duplicates, Video Copy Detection, Web Video, Content, Context, Local
Points, Novelty and Redundancy Detection, Similarity Measure, Data-driven, Video
Retreival, Social Web, Bag of Word
Southwest Jiaotong University and City University of Hong Kong.