Near-Duplicate Web Video Detection

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.

Keywords: 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