Dynamic Scene Classification Using Spatial and Temporal Cues

Arun Balajee Vasudevan, Srikanth Muralidharan, Shiva Pratheek Chintapalli, Shanmuganathan Raman; Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops, 2013, pp. 803-810

Abstract


A real world scene may contain several objects with different spatial and temporal characteristics. This paper proposes a novel method for the classification of natural scenes by processing both spatial and temporal information from the video. For extracting the spatial characteristics, we build spatial pyramids using the spatial pyramid matching (SPM) algorithm on SIFT descriptors while for the motion characteristics, we introduce a five dimensional feature vector extracted from the optical flow field. We employ SPM on combined SIFT and motion feature descriptors to perform classification. We demonstrate that the proposed approach shows significant improvement in scene classification as compared to the SPM algorithm on SIFT spatial feature descriptors alone.

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[bibtex]
@InProceedings{Balajee_2013_ICCV_Workshops,
author = {Arun Balajee Vasudevan and Srikanth Muralidharan and Shiva Pratheek Chintapalli and Shanmuganathan Raman},
title = {Dynamic Scene Classification Using Spatial and Temporal Cues},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}