并行分层二维多速度运动检测模型
Two-Dimensional Motion Detection Model with Parallel and Layered Multi-Velocity Channel
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摘要: 提出了一个新的两阶段二维多速度运动检测模型.该模型首先利用基于乘积侧抑制 速度检测子MIVD的一维速度检测特性,构成了一维多速度运动感知层.检测出一维速度信 息,然后利用胞神经网络(CNN)模拟皮层功能柱问的局部动态交互,完成多速度二维运动检 测.实验证明,这种分层并行多频道模型是对初级视觉运动感知的良好建模.应用这种模型可 以实现基于"运动信息驱动"的注意力集中机制,也可用于构成视觉高层反馈的"目的驱动"机 制.Abstract: A new two-step 2-D motion detection model is presented. A 1-D multivelocity motion detection layer is constructed based on the 1-D velocity detection feature of MIVD. A multi-velocity 2-D motion perception can be achieved by means of the good construction feature of cellular neural networks (CNN) to emulate the local dynamic interactions of cortex function columns. The experiment shows that this parallel and layered multi-velocity model is good at early vision motion perception. By using the model, the attention focus mechanism based on "motion information drive" can be realized, and the model can also be used as a part of "objectivedrive" mechanism in high level feedback of vision system.
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Key words:
- Early vision /
- motion perception /
- lateral inhibition /
- cellular neural networks /
- sensors fusion
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