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The small vibration of the eye ball, which occurs when we fix our gaze on an object, is called “fixational eye movement.” It has been reported that this vibration may work not only as a fundamental function to preserve photosensitivity but also as a clue to image analysis, for example contrast enhancement and edge detection. This mechanism can be interpreted as an instance of stochastic resonance, which is inspired by biology, more specifically by neuron dynamics. Moreover, researches for a depth recovery method using camera motions based on an analogy of fixational eye movement are in progress. In this study, using camera motions especially corresponding to the smallest type of fixational eye movement called “tremor.” We have constructed the algorithms which are defined as a differential form, i.e. spatio-temporal derivatives of successive two images are analyzed. However, in these methods, observed noise of derivatives causes serious recovering error. Therefore, we newly examine a method in which a lot of images captured with the same camera motions are integrated and the observed local image blurring is analyzed for extracting depth information, and confirm its effectiveness.

DEPTH PERCEPTION MODEL EXPLOITING BLURRING CAUSED BY RANDOM SMALL CAMERA MOTIONS