KEYNOTE: Sensor Design Technology

ISS-115
3D-IC smart image sensors, Laurent Millet¹ and Stephane Chevobbe²; ¹CEA/LETI and ²CEA/LIST (France)

Laurent Millet received his MS in electronic engineering from PHELMA University, Grenoble, France, in 2008. Since then, he has been with CEA LETI, Grenoble, in the smart ICs for image sensor and display laboratory (L3I), where he leads projects in analog design on infra-red and visible imaging. His first work topic was high-speed pipeline analog to digital converter for infra-red image sensors. His current field of expertise is 3-D stacked integration technology applied to image sensors, in which he explores highly parallel topologies for high speed and very high speed vision chips, by combining fast readout and near sensor digital processing.

PANEL: Sensors Technologies for Autonomous Vehicles

This session is jointly sponsored by: Autonomous Vehicles and Machines 2020, and Imaging Sensors and Systems 2020.

Imaging sensors are at the heart of any self-driving car project. However, selecting the right technologies isn't simple. Competitive products span a gamut of capabilities including traditional visible-light cameras, thermal cameras, lidar, and radar. Our session includes experts in all of these areas, and in emerging technologies, who will help us understand the strengths, weaknesses, and future directions of each. Presentations by the speakers listed below will be followed by a panel discussion.

Introduction: David Cardinal, ExtremeTech.com, Moderator

David Cardinal has had an extensive career in high-tech, including as a general manager at Sun Microsystems and co-founder and CTO of FirstFloor Software and Calico Commerce. More recently he operates a technology consulting business and is a technology journalist, writing for publications including PC Magazine, Ars Technica, and ExtremeTech.com.

LiDAR for Self-driving Cars: Nikhil Naikal, VP of Software Engineering, Velodyne

Nikhil Naikal is the VP of software engineering at Velodyne Lidar. He joined the company through their acquisition of Mapper.ai where he was the founding CEO. At Mapper.ai, Naikal recruited a skilled team of scientists, engineers and designers inspired to build the next generation of high precision machine maps that are crucial for the success of self-driving vehicles. Naikal developed his passion for self driving technology while working with Carnegie Mellon University’s Tartan Racing team that won the DARPA Urban Challenge in 2007 and honed his expertise in high precision navigation while working at Robert Bosch research and subsequently Flyby Media, which was acquired by Apple in 2015. Naikal holds a PhD in electrical engineering from UC Berkeley, and a Masters in robotics from Carnegie Mellon University.

Challenges in Designing Cameras for Self-driving Cars: Nicolas Touchard, VP of Marketing, DXOMARK

Nicolas Touchard leads the development of new business opportunities for DXOMARK, including the recent launch of their new Audio Quality Benchmark, and innovative imaging applications including automotive. Starting in 2008 he led the creation of dxomark.com, now a reference for scoring the image quality of DSLRs and smartphones. Prior to DxO, Nicolas spent 15+ years at Kodak managing international R&D teams, where he initiated and headed the company's worldwide mobile imaging R&D program.

Using Thermal Imaging to Help Cars See Better: Mike Walters, VP of Product Management for Thermal Cameras, FLIR Systems

Abstract: The existing suite of sensors deployed on autonomous vehicles today have proven to be insufficient for all conditions and roadway scenarios. That’s why automakers and suppliers have begun to examine complementary sensor technology, including thermal imaging, or long-wave infrared (LWIR). This presentation will explore and show how thermal sensors detect a different part of the electromagnetic spectrum compared to other existing sensors, and thus are very effective at detecting living things, including pedestrians, and other important roadside objects in challenging conditions such as complete darkness, in cluttered city environments, in direct sun glare, or in inclement weather such as fog or rain.

Mike Walters has spent more than 35 years in Silicon Valley, holding various executive technology roles at HP, Agilent Technologies, Flex and now FLIR Systems Inc. Mike currently leads all product management for thermal camera development, including for autonomous automotive applications. Mike resides in San Jose and he holds a masters in electrical engineering from Stanford University.

Radar's Role: Greg Stanley, Field Applications Engineer, NXP Semiconductors

Abstract: While radar is already part of many automotive safety systems, there is still room for significant advances within the automotive radar space. The basics of automotive radar will be presented, including a description of radar and the reasons radar is different from visible camera, IR camera, ultrasonic and lidar. Where is radar used today, including L4 vehicles? How will radar improve in the no-too-distant future?

Greg Stanley is a field applications engineer at NXP Semiconductors. At NXP, Stanley supports NXP technologies as they are integrated into automated vehicle and electric vehicle applications. Prior to joining NXP, Stanley lived in Michigan where he worked in electronic product development roles at Tier 1 automotive suppliers, predominately developing sensor systems for both safety and emissions related automotive applications.

Tales from the Automotive Sensor Trenches: Sanjai Kohli, CEO, Visible Sensors, Inc.

Abstract: An analysis of markets and revenue for new tech companies in the area of radar sensors for automotive and robotics.

Sanjai Kohli has been involved in creating multiple companies in the area of localization, communication, and sensing. Most recently Visible Sensors. He has been recognized for his contributions in the industry and is a Fellow of the IEEE.

Auto Sensors for the Future: Alberto Stochino, Founder and CEO, Perceptive

Abstract: The sensing requirements of Level 4 and 5 autonomy are orders of magnitude above the capability of today’s available sensors. A more effective approach is needed to enable next-generation autonomous vehicles. Based on experience developing some of the world most precise sensors at LIGO, AI silicon at Google, and autonomous technology at Apple, Perceptive is reinventing sensing for Autonomy 2.0.

Alberto Stochino is the founder and CEO of Perceptive, a company that is bringing cutting edge technology first pioneered in gravitational wave observatories and remote sensing satellites into autonomous vehicles. Stochino has a PhD in physics for his work on the LIGO observatories at MIT and Caltech. He also built instrumental ranging and timing technology for NASA spacecraft at Stanford and the Australian National University. Before starting Perceptive in 2017, Stochino developed autonomous technology at Apple.

KEYNOTE: Imaging Systems and Processing

This session is jointly sponsored by: The Engineering Reality of Virtual Reality 2020, Imaging Sensors and Systems 2020, and Stereoscopic Displays and Applications XXXI.

Abstract: Medical imaging is used extensively world-wide to visualize the internal anatomy of the human body. Since medical imaging data is traditionally displayed on separate 2D screens, it needs an intermediary or well trained clinician to translate the location of structures in the medical imaging data to the actual location in the patient’s body. Mixed reality can solve this issue by allowing to visualize the internal anatomy in the most intuitive manner possible, by directly projecting it onto the actual organs inside the patient. At the Incubator for Medical Mixed and Extended Reality (IMMERS) in Stanford, we are connecting clinicians and engineers to develop techniques that allow to visualize medical imaging data directly overlaid on the relevant anatomy inside the patient, making navigation and guidance for the clinician both simpler and safer. In this presentation I will talk about different projects we are pursuing at IMMERS and go into detail about a project on mixed reality neuronavigation for non-invasive brain stimulation treatment of depression. Transcranial Magnetic Stimulation is a non-invasive brain stimulation technique that is used increasingly for treating depression and a variety of neuropsychiatric diseases. To be effective the clinician needs to accurately stimulate specific brain networks, requiring accurate stimulator positioning. In Stanford we have developed a method that allows the clinician to “look inside” the brain to see functional brain areas using a mixed reality device and I will show how we are currently using this method to perform mixed reality-guided brain stimulation experiments.

ISS-189
Mixed reality guided neuronavigation for non-invasive brain stimulation treatment, Christoph Leuze, Stanford University (United States)

Christoph Leuze is a research scientist in the Incubator for Medical Mixed and Extended Reality at Stanford University where he focuses on techniques for visualization of MRI data using virtual and augmented reality devices. He published BrainVR, a virtual reality tour through his brain and is closely working with clinicians on techniques to visualize and register medical imaging data to the real world using optical see-through augmented reality devices such as the Microsoft Hololens and the Magic Leap One. Prior to joining Stanford, he worked on high-resolution brain MRI measurements at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, for which he was awarded the Otto Hahn medal by the Max Planck Society for outstanding young researchers.