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Accuracy and Tuning of Flow Parsing for Visual Perception of Object Motion During Self-Motion

机译:自运动过程中对象运动的视觉感知的流解析的精度和调整

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How do we perceive object motion during self-motion using visual information alone? Previous studies have reported that the visual system can use optic flow to identify and globally subtract the retinal motion component resulting from self-motion to recover scene-relative object motion, a process called flow parsing. In this article, we developed a retinal motion nulling method to directly measure and quantify the magnitude of flow parsing (i.e., flow parsing gain) in various scenarios to examine the accuracy and tuning of flow parsing for the visual perception of object motion during self-motion. We found that flow parsing gains were below unity for all displays in all experiments; and that increasing self-motion and object motion speed did not alter flow parsing gain. We conclude that visual information alone is not sufficient for the accurate perception of scene-relative motion during self-motion. Although flow parsing performs global subtraction, its accuracy also depends on local motion information in the retinal vicinity of the moving object. Furthermore, the flow parsing gain was constant across common self-motion or object motion speeds. These results can be used to inform and validate computational models of flow parsing.
机译:我们仅凭视觉信息如何感知自我运动过程中的物体运动?先前的研究报告说,视觉系统可以使用光流来识别并全局减去自运动产生的视网膜运动分量,以恢复场景相对的物体运动,这一过程称为流解析。在本文中,我们开发了一种视网膜运动清零方法,可以直接测量和量化各种情况下的流解析(即流解析增益)的大小,以检查流解析的准确性和调整,以便在自感知过程中对物体运动进行视觉感知。运动。我们发现,在所有实验中,所有显示器的流量解析增益均低于1。并且增加的自运动和物体运动速度不会改变流解析增益。我们得出结论,仅视觉信息不足以准确感知自我运动过程中相对于场景的运动。尽管流解析执行全局减法,但其准确性还取决于运动对象视网膜附近的局部运动信息。此外,流解析增益在常见的自运动或物体运动速度上是恒定的。这些结果可用于通知和验证流解析的计算模型。

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