SST: Minimally-Attended Integrated Visual Surveillance Network

该传感器方案侧重于为最少有人参与的视觉监控网络开发感官信息处理前端。我们打算在片上系统架构中使用混合信号硬件计算方法。图像处理算法在焦平面上实现，使用工作在微瓦功率级别的紧凑电路，以最大限度地减少电池重量和外形因素。此外，感官前端必须表现出操作自主性(即决策)和稳健性(即对环境条件的变化)。智能优点：拟议的系统将用计算传感器取代传统的计算机视觉系统(相机、数字化仪和处理器)。使用宽动态范围成像，并带有局部增益控制，绕过了标准相机的限制。时空特征提取被用来突出运动目标。利用硅中的核学习来识别由特征形成的形状；基于目标与预编程形状的相似性来生成警报。如果没有这些类型的智能、超低功耗、紧凑的成像和计算微系统，实际的视觉监控传感器网络可能无法实现。广泛的影响：传感器主要用于监控人力有限的大片偏远地区，如边境巡逻。这项工作的多学科性质将导致发展一条管道，培养具有在现代高科技行业和学术界取得成功所需的广泛技能的学生、教育工作者和研究人员。他们的教育将包括接触国土安全、隐私权和国际法方面的问题。

This Sensor proposal focuses on the development of sensory information processing front-ends for a minimally-attended visual surveillance network. We intend to use mixed-signal hardware computation methods in a system-on-a-chip architecture. Image processing algorithms are implemented at the focal-plane, using compact circuits that operate at microwatt power levels to minimize battery weight and form factor. Furthermore, the sensory front-end must demonstrate operational autonomy (i.e. in decision making) and robustness (i.e. to changes in environmental conditions).Intellectual Merit: The proposed system will replace traditional computer vision systems (cameras, digitizers and processors) with a computational sensor. Using wide-dynamic range imaging, with local gain control, circumvents the limitations of standard cameras. Spatiotemporal feature extraction is used to highlight moving targets. The shape formed by the features is identified using kernel learning in silicon; alarms are generated based on the similarity of the targets to preprogrammed shapes. Without these types of smart, ultra-low power, compact imaging and computational microsystems, practical sensor networks for visual surveillance may not be realizable.Broader Impact: The sensors are primarily intended for surveillance of large, remotely located areas, where limited manpower is available, e.g. border patrolling. Their low power and small size obviates a variety of mobile applications.The multi-disciplinary nature of this work will result in the development a pipeline of students, educators and researchers with the broad skills required to succeed in modern high technology industry and academics. Their education will be rounded with exposure to issues in homeland security, privacy rights and international law.