An electronic implementation of a saccadic vision system consisting of a CMOS image sensor ("the eye'y mounted on a mechanical servomotor ("fhe neck'y is presented. The camera first surveys the wide-angle scene at low-resolution ($A XGA), and then switches to a smaller, higher-resolution (SXGA) subwindow for more detailed inspection of salient areas. Image processing on the low-resolution scene quickly extracts the locations of objects of interest against a cluttered background. A saliency map is then generated to plot the regions of interest that require the attention of the high-resolution fovedsubwindow.Saccadic jumps are performed electronically by the camera to quickly redirect the subwindow between salient points.In this paper we discuss the design issues involved in the construction of our system protorype (including image processing strategies employed fa achieve realtime feature extraction), and we present the preliminaiy results of our tests using theprototyge.
The human vision system (HVS) is remarkably robust against eye distortions. Through a combination of eye movements and visual feedback, the HVS can often appropriately interpret scene information acquired from flawed optics.Inspired by biological systems, we have built an electronically and mechanically reconfigurable "saccadic" camera system. The saccadic camera is designed to efficiently examine scenes through foveated imaging, where scrutiny is reserved for salient regions of interest. The system's "eye" is an electronic image sensor used in multiple modes of resolution. We use a subwindow set at high resolution as the system's fovea, and capture the remaining visual field at a lower resolution. The ability to program the subwindow's size and position provides an analog to biological eye movements. Similarly, we can program the system's mechanical components to provide the "neck's" locomotion for modified perspectives.In this work, we use the saccadic camera to develop a "work-around" routine in response to possible degradations in the camera's lens. This is particularly useful in situations where the camera's optics are exposed to harsh conditions, and cannot be easily repaired or replaced. By exploiting our knowledge of the image sensor's electronic coordinates relative to the camera's mechanical movement, the system is able to develop an empirical distortion model of the image formation process. This allows the saccadic camera to dynamically adapt to changes in its image quality.
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