Robust video sequence retrieval using a novel object-based T2D-histogram descriptor

Due to the tremendous growth in the number of digital videos, the development of video retrieval algorithms that can perform efficient and effective retrieval task is indispensable. In this paper, we propose a high-level motion activity descriptor, object-based transformed 2D-histogram (T2D-histogram), which exploits both spatial and temporal features to characterize video sequences in a semantics-based manner. The discrete cosine transform (DCT) is applied to convert the object-based 2D-histogram sequences from the time domain to the frequency domain. Using this transform, the original high-dimensional time domain features used to represent successive frames are significantly reduced to a set of low-dimensional features in frequency domain. The energy concentration property of DCT allows us to use only a few DCT coefficients to effectively capture the variations of moving objects. Having the efficient scheme for video representation, one can perform video retrieval in an accurate and efficient way.