Robust models for optic flow coding in natural scenes inspired by insect biology.
Robust models for optic flow coding in natural scenes inspired by insect biology.
复制标题
在受昆虫生物学启发的自然场景中进行光流编码的强大模型。
DOI：
10.1371/journal.pcbi.1000555
复制
发表时间：
2009-11
影响因子：
4.3
通讯作者：
O'Carroll, David C.
中科院分区：
文献类型：
--
作者：
Brinkworth, Russell S. A.;O'Carroll, David C.
从视觉世界中提取准确的自运动信息是一个难题，生物有机体利用非线性处理已经非常有效地解决了这个问题。以前基于相关机制的仿生运动检测模型一直受到其对图像不良特性（例如对比度，图像之间差异很大）的敏感性所引起的问题的困扰。在这里，我们提出了一个具有多个层次的非线性动态自适应组件的模型，直接基于果蝇大脑视觉运动通路内神经元的已知或可疑反应。通过在现实的高动态范围条件下测试模型，我们表明，添加这些元素使得运动检测模型在各种图像、速度和加速度上都具有鲁棒性。此外，整个系统的性能超过了各个组件提供的增量改进，这表明处理阶段之间存在有益的非线性交互。该模型背后的算法可以在数字或模拟硬件中实现，包括神经形态模拟 VLSI，但由于其动态非线性操作而无法解析解决方案。该算法的成功应用可应用于国防和民用微型自主系统的开发，包括机器人、微型无人机和防撞传感器。构建在各种环境中稳定工作的人工视觉系统一直很困难，因为系统通常只能在有限的条件下表现良好。相比之下，动物视觉在极其多变的情况下也能有效发挥作用。许多模拟生物视觉的尝试都取得了有限的成功，通常是因为对神经编码的多个看似适当的近似导致了系统的受损。我们已经构建了昆虫视觉通路中运动处理的完整模型，尽可能详细地结合了已知或可疑的元素。我们发现，只有当所有元素都存在时，系统才能稳健运行，元素的减少或删除会极大地限制性能。这种新算法的实现可以为人工导航系统提供非常有用且鲁棒的速度估计器。
The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. Building artificial vision systems that work robustly in a variety of environments has been difficult, with systems often only performing well under restricted conditions. In contrast, animal vision operates effectively under extremely variable situations. Many attempts to emulate biological vision have met with limited success, often because multiple seemingly appropriate approximations to neural coding resulted in a compromised system. We have constructed a full model for motion processing in the insect visual pathway incorporating known or suspected elements in as much detail as possible. We have found that it is only once all elements are present that the system performs robustly, with reduction or removal of elements dramatically limiting performance. The implementation of this new algorithm could provide a very useful and robust velocity estimator for artificial navigation systems.
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DOI：
10.1109/34.250844
发表时间：
1993-12-01
影响因子：
23.6
作者：
FLEET, DJ;JEPSON, AD
通讯作者：
JEPSON, AD
影响因子：
1.2
作者：
BORST, A;EGELHAAF, M;HAAG, J
通讯作者：
HAAG, J
影响因子：
1.8
作者：
Brinkworth, Russell S. A.;Mah, Eng-Leng;O'Carroll, David C.
通讯作者：
O'Carroll, David C.
DOI：
10.1007/bf00612703
发表时间：
1982-01-01
期刊：
JOURNAL OF COMPARATIVE PHYSIOLOGY
影响因子：
--
作者：
DUBS, A
通讯作者：
DUBS, A
影响因子：
1.9
作者：
EGELHAAF, M;BORST, A
通讯作者：
BORST, A