We present a foveated object detector (FOD) as a biologically-inspired
alternative to the sliding window (SW) approach which is the dominant method of
search in computer vision object detection. Similar to the human visual system,
the FOD has higher resolution at the fovea and lower resolution at the visual
periphery. Consequently, more computational resources are allocated at the
fovea and relatively fewer at the periphery. The FOD processes the entire
scene, uses retino-specific object detection classifiers to guide eye
movements, aligns its fovea with regions of interest in the input image and
integrates observations across multiple fixations. Our approach combines modern
object detectors from computer vision with a recent model of peripheral pooling
regions found at the V1 layer of the human visual system. We assessed various
eye movement strategies on the PASCAL VOC 2007 dataset and show that the FOD
performs on par with the SW detector while bringing significant computational
cost savings.

本文提出了一种生物启发的凹视检测器（FOD）作为在计算机视觉目标检测中搜索的主要方法中滑动窗口 (SW) 方法的替代方案。这种方法通过结合现代计算机视觉中的目标检测器和人类视觉系统的 V1 层中发现的外围汇集区域的最近模型，实现了显着的计算成本节省。