Attention selection using global topological properties based on pulse coupled neural network

作者：Gu Xiaodong^*; Fang Yu; Wang Yuanyuan

来源：Computer Vision and Image Understanding, 2013, 117(10): 1400-1411.

DOI：10.1016/j.cviu.2013.05.004

• Topological properties
• Quatemion
• PCNN
• Saliency map
• Attention selection
• Hole-filter
• TPA

Topological properties are with invariance and take priority over other features, which play an important role in cognition. This paper introduces a new attention selection model called TPA (topological properties-based attention), which adopts topological properties and quaternion. In TPA, using Unit-linking PCNN (Pulse Coupled Neural Network) hole-filter expresses an important topological property (the connectivity) in visual attention selection. Meanwhile, using the quaternion Fourier transform based phase spectrum of an image or a frame in a video obtains the spatio-temporal saliency map, which shows the result of attention selection. Adjusting the weight of a topological channel can change its influence. The experimental results show that TPA reflects the real attention selection more accurately than PQFT (Phase spectrum of Quaternion Fourier Transform).

• 出版日期2013-10
• 单位复旦大学