A bioinspired 128x128 pixel dynamic-vision-sensor

This paper presents a 128x128 dynamic vision sensor. Each pixel detects temporal changes in the local illumination. A minimum illumination temporal contrast of 10% can be detected. A compact preamplification stage has been introduced that allows to improve the minimum detectable contrast over previous designs, while at the same time reducing the pixel area by 1/3. The pixel responds to illumination changes in less than 3.6μs. The ability of the sensor to capture very fast moving objects has been verified experimentally. A frame-based sensor capable to achieve this, would require at least 100K frames per second.Unión Europea FP7-ICT-2007-1-216777Ministerio de Educación y Ciencia TEC2006-11730-C03-01 (SAMANTA2)Ministerio de Educación y Ciencia TEC2009-10639- C04-01 (VULCANO)Junta de Andalucía P06- TIC-1417 (Brain System

A Comparative Evaluation of the Detection and Tracking Capability Between Novel Event-Based and Conventional Frame-Based Sensors

Traditional frame-based technology continues to suffer from motion blur, low dynamic range, speed limitations and high data storage requirements. Event-based sensors offer a potential solution to these challenges. This research centers around a comparative assessment of frame and event-based object detection and tracking. A basic frame-based algorithm is used to compare against two different event-based algorithms. First event-based pseudo-frames were parsed through standard frame-based algorithms and secondly, target tracks were constructed directly from filtered events. The findings show there is significant value in pursuing the technology further

Applications of Silicon Retinas: from Neuroscience to Computer Vision

Traditional visual sensor technology is firmly rooted in the concept of sequences of image frames. The sequence of stroboscopic images in these "frame cameras" is very different compared to the information running from the retina to the visual cortex. While conventional cameras have improved in the direction of smaller pixels and higher frame rates, the basics of image acquisition have remained the same. Event-based vision sensors were originally known as "silicon retinas" but are now widely called "event cameras." They are a new type of vision sensors that take inspiration from the mechanisms developed by nature for the mammalian retina and suggest a different way of perceiving the world. As in the neural system, the sensed information is encoded in a train of spikes, or so-called events, comparable to the action potential generated in the nerve. Event-based sensors produce sparse and asynchronous output that represents in- formative changes in the scene. These sensors have advantages in terms of fast response, low latency, high dynamic range, and sparse output. All these char- acteristics are appealing for computer vision and robotic applications, increasing the interest in this kind of sensor. However, since the sensor’s output is very dif- ferent, algorithms applied for frames need to be rethought and re-adapted. This thesis focuses on several applications of event cameras in scientific scenarios. It aims to identify where they can make the difference compared to frame cam- eras. The presented applications use the Dynamic Vision Sensor (event camera developed by the Sensors Group of the Institute of Neuroinformatics, University of Zurich and ETH). To explore some applications in more extreme situations, the first chapters of the thesis focus on the characterization of several advanced versions of the standard DVS. The low light condition represents a challenging situation for every vision sensor. Taking inspiration from standard Complementary Metal Oxide Semiconductor (CMOS) technology, the DVS pixel performances in a low light scenario can be improved, increasing sensitivity and quantum efficiency, by using back-side illumination. This thesis characterizes the so-called Back Side Illumination DAVIS (BSI DAVIS) camera and shows results from its application in calcium imaging of neural activity. The BSI DAVIS has shown better performance in the low light scene due to its high Quantum Efficiency (QE) of 93% and proved to be the best type of technology for microscopy application. The BSI DAVIS allows detecting fast dynamic changes in neural fluorescent imaging using the green fluorescent calcium indicator GCaMP6f. Event camera advances have pushed the exploration of event-based cameras in computer vision tasks. Chapters of this thesis focus on two of the most active research areas in computer vision: human pose estimation and hand gesture classification. Both chapters report the datasets collected to achieve the task, fulfilling the continuous need for data for this kind of new technology. The Dynamic Vision Sensor Human Pose dataset (DHP19) is an extensive collection of 33 whole-body human actions from 17 subjects. The chapter presents the first benchmark neural network model for 3D pose estimation using DHP19. The network archives a mean error of less than 8 mm in the 3D space, which is comparable with frame-based Human Pose Estimation (HPE) methods using frames. The gesture classification chapter reports an application running on a mobile device and explores future developments in the direction of embedded portable low power devices for online processing. The sparse output from the sensor suggests using a small model with a reduced number of parameters and low power consumption. The thesis also describes pilot results from two other scientific imaging applica- tions for raindrop size measurement and laser speckle analysis presented in the appendices

Infrared time-correlated single-photon counting

This Thesis investigates near infrared ( ~ 1550 nm) time-correlated singlephoton counting, studying the single-photon detectors and some of the potential application areas. Custom designed and fabricated InGaAs/InP single-photon avalanche diode detectors were characterised. Our devices yielded single-photon detection efficiencies of ~10 %, timing jitter of 200 ps, and noise equivalent power comparable to the best commercially available avalanche photodiodes operated in Geiger-mode. The afterpulsing phenomenon which limits the maximum count rate of InGaAs/InP single-photon avalanche diodes has been investigated in detail and activation energies calculated for the traps that cause this problem. This was found to be ~250 meV for all the devices tested, despite their differing structures and growth conditions, and points to the InP multiplication region as the likely location of the traps. Ways of reducing the effects caused by the afterpulsing phenomenon were investigated and sub-Geiger mode operation was studied in detail. This approach enabled freerunning, afterpulsing-free operation at room temperature of an InGaAs/InP singlephoton avalanche diode detector for the first time. Finally, time-of-flight photon counting laser ranging was performed using both singlephoton avalanche diodes and superconducting nanowire single-photon detectors. The use of the latter resulted in a surface to surface depth resolution of 4 mm being achieved at low average laser power at an eye-safe wavelength of 1550 nm

Workshop on Advanced Technologies for Planetary Instruments, part 1

This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. This volume contains papers presented at the Workshop on Advanced Technologies for Planetary Instruments on 28-30 Apr. 1993. This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. Over the past several years, SDIO has sponsored a significant technology development program aimed, in part, at the production of instruments with these characteristics. This workshop provided an opportunity for specialists from the planetary science and DoD communities to establish contacts, to explore common technical ground in an open forum, and more specifically, to discuss the applicability of SDIO's technology base to planetary science instruments