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A learning method for association between vision and ego-motion which is Capable of Adapting to Arbitrary Image Distortion

机译:视觉与自我运动之间的学习方法,其能够适应任意图像失真

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The present study considers how the function of vision can be constructed from the experiences of a robot. Specifically, a learning method is proposed for the association between vision and ego-motion. A novel concept of a time evolution operator on sensory inputs is introduced. The time variation of sensory inputs is obtained when the operator is applied to the current inputs. Association between the time evolution operator and the egomotion is learned. Once the learning has been performed, ego-motion can be inferred from the operator constructed from sensory inputs. The main feature of this method is that it does not use any knowledge of image construction obtained by optics and so is flexible with respect to arbitrary image distortion. This flexibility is confirmed by a computer simulation. The proposed method may be considered a method of recovery of structure and motion from motion that remains nearly unaffected by arbitrary image distortion.
机译:本研究考虑了视力的功能如何从机器人的经验构成。具体地,提出了一种学习方法,用于视觉和自我运动之间的关联。介绍了在感官输入上的时间演化运营商的新颖概念。当操作者应用于电流输入时获得感觉输入的时间变化。学习时间演化运营商与映象之间的关联。一旦进行了学习,就可以从由感觉输入构成的操作者推断出EGO运动。该方法的主要特征是它不使用由光学器件获得的图像结构的任何知识,并且相对于任意图像失真是灵活的。通过计算机仿真确认这种灵活性。所提出的方法可以被认为是一种恢复结构的方法和来自遗留的运动的运动,其几乎不受任意图像失真的影响。

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