Similarity Retrieval by Using Unique-ID-based Matrix for Video Databases
Date Issued
2004
Date
2004
Author(s)
Chang, Chun-Fei
DOI
en-US
Abstract
In this thesis, we propose a new similarity retrieval method called Unique-ID-based Video matrix (UV-matrix) to represent a symbolic video and to retrieve the videos similar to a given query video. We extended the idea behind the similarity retrieval of images in the UID matrix approach to the UV-matrix approach. Our proposed approach has two phases. First, we generate a sequence of matrices to represent the spatial relation between objects, sizes and locations of objects for a video. Second, based on these matrices, similarity retrieval can be performed by simple matrix operations from the video database for a given query video.
According to our analysis, the time complexity of the UV-matrix approach is bounded by O(n2 ´ q ´ f), where n is the number of objects in a query, q is the number of frames in a query and f is the number of frames in a database video. In comparison with 3D C-string, the UV-matrix approach has less time complexity. We also define 17 types of similarity measures. By providing various types of similarity between videos, our proposed similarity retrieval algorithm can meet the different types of user’s need. Finally, some experiments are performed to compare the performance of the 3D C-string and the UV-matrix approach.
Subjects
視訊檢索
視訊資料庫
UV-matrix
UID matrix
3D C-string
Video databases
Similarity retrieval
Type
other
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