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EETimes has published an interview with CEO of Prophesee about their event sensor technology. Some excerpts below.   Prophesee collaborated with Sony on creating the IMX636 event sensor chip.   Meaning of "neuromorphic" Most companies doing neuromorphic sensing and computing have a similar vision in mind, but implementations and strategies will be different based on varying product, market, and investment constraints. ... ... there is a fundamental belief that the biological model has superior characteristics compared to the conventional ... Markets targeted ... the sector closest to commercial adoption of this technology is industrial machine vision. ... The second key market for the IMX 636 is consumer technologies, ... the event–based camera is used alongside a full–frame camera, detecting motion ... correct any blur. Prophesee is also working with a customer on automotive driver monitoring solutions... Applications here include eye blinking detection, tracking or face tr

From arXiv.org --- You Li et al. write: Autonomous vehicles rely on perception systems to understand their surroundings for further navigation missions. Cameras are essential for perception systems due to the advantages of object detection and recognition provided by modern computer vision algorithms, comparing to other sensors, such as LiDARs and radars. However, limited by its inherent imaging principle, a standard RGB camera may perform poorly in a variety of adverse scenarios, including but not limited to: low illumination, high contrast, bad weather such as fog/rain/snow, etc. Meanwhile, estimating the 3D information from the 2D image detection is generally more difficult when compared to LiDARs or radars. Several new sensing technologies have emerged in recent years to address the limitations of conventional RGB cameras. In this paper, we review the principles of four novel image sensors: infrared cameras, range-gated cameras, polarization cameras, and event cameras . Their compa

Dr. Ryad Benosman, a professor at University of Pittsburgh believes a huge shift is coming to how we capture and process images in computer vision applications. He predicts that event-based (or, more broadly, neuromorphic) vision sensors are going to dominate in the future. Dr. Benosman will be a keynote speaker at this year's Embedded Vision Summit .  EETimes published an interview with him; some excerpts below. According to Benosman, until the image sensing paradigm is no longer useful, it holds back innovation in alternative technologies. The effect has been prolonged by the development of high–performance processors such as GPUs which delay the need to look for alternative solutions. “Why are we using images for computer vision? That’s the million–dollar question to start with,” he said. “We have no reasons to use images, it’s just because there’s the momentum from history. Before even having cameras, images had momentum.” Benosman argues, image camera–based techniques for com