Within the framework of spatiotemporal attention detection, this paper proposes an efficient method for focus of attention (FOA) detection which involves combining adaptively the spatial and motion attention to form an overall attention map. Without computing motion explicitly, it detects motion attention using the rank deficiency of grayscale gradient tensors. We also propose an attention-driven shot matching method using primarily FOA. Experimental results demonstrate the effectiveness of the proposed FOA detection method and the proposed shot matching approach outperforms other published methods.
['Shan Li', 'Moon-Chuen Lee']
An Efficient Spatiotemporal Attention Model and Its Application to Shot Matching