Video texture indexing using spatio-temporal wavelets

Abstract

In this paper, we present a new compact spatio-temporal texture descriptor designed for indexing dynamic video content. Video texture provides a way to characterize spatio-temporal features such as those corresponding to splashing water, flying birds, blowing trees, and so forth, which are not easily characterized by static feature descriptors. The video texture descriptor measures the 3-D wavelet energy corresponding to spatio-temporal-frequency subbands of video segments. The wavelet energy captures the texture patterns as they unfold simultaneously along the spatial and temporal dimensions. In this paper, we describe the process for extracting video texture features and investigate different methods of constructing video texture descriptors from 3-D wavelet energy. We evaluate the video texture descriptors in retrieval experiments and show performance improvements compared to methods based on traditional texture descriptors.