Neuromorphic binocular vision system for real-time disparity estimation
Neuromorphic binocular vision system for real-time disparity estimation
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DOI：
10.1109/robot.2007.364229
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发表时间：
2007-04
期刊：
影响因子：
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通讯作者：
K. Shimonomura;T. Kushima;T. Yagi
中科院分区：
文献类型：
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作者：
K. Shimonomura;T. Kushima;T. Yagi
我们描述了一种双目视觉系统，该系统模拟初级视觉皮层（V1）神经元回路中的视差计算。该系统由两组硅视网膜和简单的单元芯片组成，分别对应双目视觉和现场可编程门阵列（FPGA）电路。这种安排模仿了大脑视觉系统的层次结构。硅视网膜是一种模拟超大规模集成（aVLSI）电路，拥有类似于脊椎动物视网膜感受野的拉普拉斯-高斯空间滤波器。简单细胞芯片通过聚合硅视网膜的多个像素，生成类似于 V1 中简单细胞的方向选择性感受野的类 Gabor 空间滤波器。 FPGA接收两个简单单元芯片对应的左右眼双眼输入的输出，并根据视差能量模型实时计算双眼视差。该系统并行提供调整为五种不同视差的输出图像。通过比较这些视差能量输出获得视差图。由于aVLSI的并行和模拟计算与硬连线数字电路的逐像素计算相结合，本系统可以使用紧凑的硬件和低功耗实时有效地计算双眼视差。
We describe a binocular vision system that emulates disparity computation in the neuronal circuit of the primary visual cortex (V1). The system consists of two sets of silicon retinas and simple cell chips that correspond to the binocular vision and field programmable gate array (FPGA) circuit. This arrangement mimics the hierarchical architecture of the visual system of the brain. The silicon retina is an analog very large scale integrated (aVLSI) circuit and possesses a Laplacian-Gaussian-like spatial filter similar to the receptive field of the vertebrate retina. The simple cell chip generates a Gabor-like spatial filter similar to the orientation-selective receptive field of the simple cell in V1 by aggregating several pixels of the silicon retina. The FPGA receives the outputs from the two simple cell chips corresponding to binocular inputs from the left and right eyes and calculates the binocular disparity in real-time based on the disparity energy model. The system provides output images tuned to five different disparities in parallel. The disparity map is obtained by comparing these disparity energy outputs. Due to the combination of the parallel and analog computation of the aVLSIs and the pixel-wise computation with hard-wired digital circuits, the present system can efficiently compute the binocular disparity using compact hardware and low power dissipation in real-time.