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BusinessWire: ON Semiconductor announces X-Class image sensor platform, which allows a single camera design supporting multiple sensors across the platform. The first devices in the new platform are the 12MP XGS 12000 and 4k / UHD resolution XGS 8000 sensors for machine vision, intelligent transportation systems, and broadcast imaging applications.

The X-Class image sensor platform supports multiple CMOS pixel architectures within the same image sensor frame. This allows a single camera design to support multiple product resolutions and different pixel functionality, such as larger pixels that trade resolution at a given optical format for higher imaging sensitivity, designs optimized for low noise operation to increase DR, and more. By supporting these different pixel architectures through a common high bandwidth, low power interface, camera manufacturers can leverage existing parts inventory and accelerate time to market for new camera designs.

The initial devices in the X-Class family, the XGS 12000 and XGS 8000, are based on the first pixel architecture to be deployed in this platform – a 3.2 µm global shutter CMOS pixel. The XGS 12000 12 MP device is planned to be available in two speed grades – one that fully utilizes 10GigE interfaces by providing full resolution speeds up to 90 fps, and a lower price version providing 27 fps at full resolution that aligns with the bandwidth available from USB 3.0 computer interfaces. The XGS 8000 is also planned to be available in two speed grades (130 and 75 fps) for broadcast applications.

“As the needs of industrial imaging applications such as machine vision inspection and industrial automation continue to advance, the design and performance of the image sensors targeting this growing market must continue to evolve,” said Herb Erhardt, VP and GM, Industrial Solutions Division, Image Sensor Group at ON Semiconductor. “With the X-Class platform and devices based on the new XGS pixel, end users have access to the performance and imaging capabilities they need for these applications, while camera manufacturers have the flexibility they require to develop next-generation camera designs for their customers both today and in the future.”

The XGS 12000 and XGS 8000 will begin sampling in the 2Q2018, with production availability scheduled for the 3Q2018. Additional devices based on the 3.2 µm XGS pixel as well as products based on other pixel architectures are planned for the X-Class family in the future.


BusinessWire: ON Semiconductor also announces a fully AEC-Q100 qualified version of its circa-2016 2.1 MP CMOS sensor, AR0237 for the OEM-fitted dash cam or before-market in-car DVR market.

The AR0237AT is a cost-optimized, automotive qualified version of the same sensor that can operate across the full automotive operating temperature range of -40°C to +105°C and deliver the right performance at the right price point. The low-light performance of the AR0237AT is improved when it is coupled to a Clarity+ enabled DVR processor. ON Semiconductor’s Clarity+ technology employs filtering to optimize the SNR of automotive imaging solutions, which can deliver an additional 2X increase in light capture.

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Adafruit publishes a datasheet of its distance sensor using ST SPAD-based ToF chip VL53L0X.

Update: Upon a closer look, the official ST VL530L0X datasheet has all these tables with the performance data.

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MDPI Sensors publishes a paper from a group of Japanese universities "The Dynamic Photometric Stereo Method Using a Multi-Tap CMOS Image Sensor" by Takuya Yoda, Hajime Nagahara, Rin-ichiro Taniguchi, Keiichiro Kagawa, Keita Yasutomi, and Shoji Kawahito. The paper proposes using of a 4-tap ToF sensor developed in Shizuoka University for 3D imaging in a different way:

"The photometric stereo method enables estimation of surface normals from images that have been captured using different but known lighting directions. The classical photometric stereo method requires at least three images to determine the normals in a given scene. However, this method cannot be applied to dynamic scenes because it is assumed that the scene remains static while the required images are captured. In this work, we present a dynamic photometric stereo method for estimation of the surface normals in a dynamic scene. We use a multi-tap complementary metal-oxide-semiconductor (CMOS) image sensor to capture the input images required for the proposed photometric stereo method. This image sensor can divide the electrons from the photodiode from a single pixel into the different taps of the exposures and can thus capture multiple images under different lighting conditions with almost identical timing. We implemented a camera lighting system and created a software application to enable estimation of the normal map in real time. We also evaluated the accuracy of the estimated surface normals and demonstrated that our proposed method can estimate the surface normals of dynamic scenes."

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Techinsights publishes reverse engineering report of Samsung 0.9um Tetracell pixel sensor:

There are many reasons we are excited about the Samsung S5K2X7SP 0.9µm Image Sensor, including Samsung’s claims about it:

• “Slim 2X7 with Tetracell technology” (.9um, 24MP)
• The first 0.9 µm generation pixels in mass production
• Targeting both front and rear cameras

As well as its noted technology features:

Improved ISOCELL technology with deeper deep trench isolation

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Broadcom-Avago unveils its first ToF sensor product. The AFBR-S50MV85G has quite a nice spec:

"The AFBR-S50 is Broadcom's multipixel distance and motion measurement sensor based on the optical time-of-flight principle. It supports up to 3000 frames per second with up to 16 illuminated pixels.

This sensor has been developed with a special focus on industrial sensing applications and gesture sensing with the need for high speed, small size and very low power consumption. Through its best-in-class ambient light suppression of up to 200k Lux, its use in outside environments is no problem.

The technology has been optimized to measure distances up to 10m (black target) with an accuracy of < 1 percent on a wide variety of surfaces. It works equally well on white, black, colored and metallic reflective surfaces.

The module has an integrated 850nm laser light source and uses a single voltage supply of 5V; the data is transferred via a digital SPI interface."


Broadcom presented the new ToF sensor in February 2018 at Embedded World trade fair in Nuremberg, Germany:

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New Imaging Technologies presents an affordable CMOS sensor (12 bits) HV2061 with native HDR capability (140dB intra-scene and inter-scene) offering three operating modes; rolling, global and differential (subtraction of two frames in pixel). Its performance is supposed to allow users to get local illumination in real time for many computer vision application such as biometrics, gesture detection, sense & avoid, etc.:

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AutoSens publishes Chronocam-Prophesee CTO and Co-Founder Christoph Posch presentation "Event-based vs conventional cameras for ADAS and autonomous driving applications:"

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Multianalytics Blog publishes nice videos of image sensor performance progress over the years:

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BusinessWire: AEye announces it has been awarded foundational patents for its solid state MEMS-based LiDAR. These include 71 claims covering AEye inventions ranging from an approach to dynamic scan and shot pattern for LiDAR transmissions to the ability to control and shape each laser pulse and methods for interrogating each voxel within a point cloud. These inventions are said to contribute significant performance improvements for the iDAR perception system: improving range by 400%; increasing speed by 20x; and boosting object classification accuracy while reducing laser interference.

"AEye's groundbreaking iDAR system is the first to use intelligent data capture to enable rapid perception and path planning,” said Elliot Garbus, former VP of Transportation Solutions at Intel. “Most LiDAR systems function at only 10Hz, while the human visual cortex processes at 27Hz. Autonomous vehicles need perception systems that work at least as fast as humans. iDAR is the first and only perception system to consistently deliver performance of at least 30-50Hz. Better quality information, faster. This is a game changer for the autonomous vehicle market.”

“Leveraging the inventions covered by our patents, we created the worlds first intelligent agile LiDAR – enabling us to interrogate a point cloud as individual voxels and control each one using multiple levers,” said Allan Steinhardt, Chief Scientist at AEye. “Traditional systems only adapt on frame size or placement. In addition to frame size and placement, Agile LiDAR – a core feature of the iDAR perception system – allows us to dynamically control frame pattern, pulse tuning, pulse shaping, pulse energy and other critical dimensions that enable embedded AI.”

AEye’s first iDAR-based product, the AE100 artificial perception system, will be available this summer to OEMs and Tier 1s launching autonomous vehicle initiatives.

The granted patents are probably US9885778 and US9897689 proposing the adaptive scanning so that the laser energy is spent in a more economical way only on "interesting spots", for the most part:

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Trendforce publishes its analysis of 3D sensing in smartphones:

"According to Peter Huang, analyst at TrendForce, there are three major technical barriers in producing 3D sensing modules at present. First, it is not easy to manufacture high-efficiency VCSELs, and the current electrical-to-optical power conversion efficiency is only about 30% on average. Second, the production of diffractive optical elements (DOE), a necessary component of Structured Light technology, and CMOS image sensor (CIS) in infrared cameras, require sophisticated technology. Third, the issue of thermal expansion also needs to be taken into consideration, making 3D sensing module assembly even more challenging. In sum, all these factors contribute to low yield of 3D sensing modules.

Therefore, it is estimated that only up to two Android phone vendors, most likely Huawei and Xiaomi, would adopt 3D sensing modules in 2018 with very limited shipments. Thus, Apple will remain the major smartphone company that adopts 3D sensing this year. It is estimated that the production volume of smartphones equipped with 3D sensing modules will reach 197 million units by the end of 2018, of which 165 million units will be iPhones. In addition, the market value of 3D sensing module in 2018 is estimated to be about US$5.12 billion, with iPhones alone accounting for 84.5% of the entire value. By 2020, the market value is estimated to reach US$10.85 billion, and the CAGR will be 45.6% from 2018 to 2020."

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Wiley Strategic Entrepreneurship Journal publishes a paper "When dinosaurs fly: The role of firm capabilities in the ‘avianization’ of incumbents during disruptive technological change" by Raja Roy, Curba Morris Lampert, and Irina Stoyneva.

"Research Summary: We investigate the image sensor industry in which the emergence of CMOS sensors challenged the manufacturers of CCD sensors. Although this disruptive technological change led to the demise of CCD technology, it also led to avianization — or strategic renewal — for some incumbents, similar to how some dinosaurs survived the mass Cretaceous-Tertiary extinction by evolving into birds. We find that CCD manufacturers that did avianize were preadapted to the disruptive CMOS technology in that they possessed relevant complementary technologies and access to in-house users that allowed them to strategically renew themselves.

Managerial Summary: We investigate the transition from CCD to CMOS image sensors in the digital image sensor industry. Although the emergence of CMOS sensors was disruptive to CCD sensors, we find that CCD sensor manufacturers such as Sony and Sharp successfully transitioned to manufacturing CMOS sensors. Contrary to popular press and prior academic research characterizing disruptive change as being a source of failure for large firms, our research reveals that firms that possess relevant complementary technologies and have access to in-house users are able to strategically renew themselves in the face of a disruptive threat."

While the main paper is behind a paywall, the supplementary material is openly available.

The complementary technologies (CT) are said to enable the CCD companies to win a place on CMOS sensor market:

• Global or electronic shuttering
• Microlenses
• CDS
• Lightpipe or light shield
• Hole Accumulation Diode (HAD)

Another key condition for successful transition to CMOS technology is an access to in-house users. It is used to explain Kodak demise:

"The lack of access to in-house users at Kodak was consistent with its corporate strategy. According to George Fisher, ex-CEO, Eastman Kodak was a ‘horizontal firm because in a digital world, it is much more important to pick out horizontal layers where you have distinctive capabilities. In the computer world, one company specializes in microprocessors, one in monitors, and another in disk drives’ (Galaza and Fisher, 1999: 46). Chinon was eventually acquired by Kodak in 2004 (Eastman Kodak Company, 2004a) and continued to design and manufacture the point-and-shoot cameras."

Reticon/EG&G, Tektronix, and Ford Aeronutronic used to have access to in-house users but lacked relevant CTs. "We find that Reticon/EG&G, Tektronix, and Aeronutronic Ford failed to avianize themselves during the disruptive change to CMOS sensors from CCD sensors."

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AutoSens publishes Panasonic Soeren Molander presentation "Active sensing technologies for automotive applications:"

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BusinessWire: ON Semiconductor introduces a 43MP CCD in 35 mm optical format, said to be the highest CCD resolution in full-frame format. The KAI-43140 is aimed to applications such as end of line inspection of HD and UHD flat panel displays and aerial photography.

The KAI-43140 utilizes a new 4.5 µm Interline Transfer CCD (ITCCD) pixel that increases resolution by 50% compared to the prior 5.5 µm design while preserving critical imaging performance. Featuring a true electric “global” shutter, the device supports full resolution frame rates up to 4 fps through the use of flexible 1, 2, or 4 output readout architecture. The KAI-43140 shares the same package and pin definitions as the popular 29 MP KAI-29050 and KAI-29052 image sensors, allowing it to be incorporated into existing camera designs with only minor electrical changes.

“Many industrial imaging applications demand the image uniformity currently only available from CCD technology, while needing the resolution increases that require continued pixel development,” said Herb Erhardt, VP and GM, Industrial Solutions Division, Image Sensor Group at ON Semiconductor. “With the KAI-43140, camera manufacturers and end customers can continue to push the boundaries of high resolution image capture without sacrificing the image quality their applications require.”

Engineering grade versions of the KAI-43140 are now available, with production versions planned for early 3Q18.

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Pixart keeps diversifying its image sensor portfolio with some degree of success:

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SeekingAlpha publishes Himax Q4 2017 earnings call transcript. Few quotes on 3D and CMOS sensor business:

"At present, our total market is primarily the Android based smartphone. SLiM, our total – our structure light-based 3D sensing total solutions which we announced jointly with Qualcomm last August, brings together Qualcomm’s industry leading 3D algorithm with Himax’s cutting-edge design and manufacturing capabilities in optics and NIR sensors as well as our unique know-how in 3D sensing system integration.

The majority of the key technologies inside the SLiM total solution is developed and supplied by Himax ourselves. These critical technologies include, on the projector end, DOE and collimator utilizing our world leading WLO technology, a tailor-made laser driver IC, and high precision active alignment for the projector assembly; and on the receiver end, a high efficiency near-infrared CMOS image sensor. Last but not least, Himax also developed an ASIC by incorporating Qualcomm’s algorithm for 3D depth map generation. The fact that all of these critical components are developed in-house puts us in a unique leading position. It represents a very high barrier of entry for any potential competition and a much higher ASP and profit margin for us.

The Qualcomm/Himax solution is by far the highest quality 3D sensing total solution available for the Android market right now. It has the industry’s best performance in all of the dimension, 3D depth accuracy, indoor/outdoor sensitivity and power consumption. It passes the toughest eye safety standards with a proprietary glass broken detection mechanism to safeguard the user from any potential harm. Furthermore, we have the only solution to offer face recognition for secure online payment, a must-have feature for high end smartphones of the future. We are working with multiple tier-1 smartphone makers, aiming to launch 3D sensing on their premium smartphones starting the first half of 2018.

Our SLiM solution will be ready for mass production and shipment by the end of the first quarter, 2018 with an initial capacity of 2 million units per month, following some waiting period. The initial capacity is part of our Phase I expansion of $80 million. We have already achieved pretty satisfactory production yields in our internal pilot production. Given that SLiM is a highly integrated solution with ASPs much higher than those of individual components, by the time we started making shipment, it will be a major growth contributor to our top and bottom lines.

In an attempt to accelerate the adoption of 3D sensing for Android phones, in addition to SLiM, we’re also working on stereoscopic type 3D sensing as a lower costs alternative. Unlike SLiM which utilizes structure light to generate 3D, stereoscopic type uses two cameras to replicate 3D vision in nature, augmented by coded light for image depth enhancement. Both types of solutions offered by Himax operate on active NIR light source with high sensitivity NIR sensors, thus working very well even under extreme brightness or total darkness.

For 3D sensing purposes, structure light approach offers better depth precision than stereoscopic type but the cost is also higher. By introducing stereoscopic 3D sensing, we aim to bring down the cost of 3D sensing so that it can be afforded by mass market smartphone models. We are pleased to report that development of stereoscopic 3D sensing total solution for face recognition and 3D features has been under way. We are aiming to be mass production and shipment ready by Q4 of this year. Similar to our experience in SLiM, we are working with some of the most prominent ecosystem partners in developing our stereoscopic 3D total solution.

We are very update progress in due course or low costs compared to structure light their stereoscopic 3D was still represent a much higher ASP and better gross margin potential for us. Last but not least and this year CES many of our customers and partners demonstrated 3D sensing applications in IoT or promoted AR/VR and robotic related products with Himax SLiM inside and received very positive feedback. As I mentioned before, 3D sensing can have a broad range of applications that go beyond smartphone. We are very excited about the growth prospects it represents and believes 3D sensing will be our biggest long-term growth engine."

A slide from the company presentation:

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Autosens publishes a presentation "LIDAR systems for automotive: Benefits and the challenges for OEMs" by Jaguar Landrover's Andy Lewin:

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MDPI Special Issue on the 2017 International Image Sensor Workshop publishes Delft University paper "Temporal Noise Analysis of Charge-Domain Sampling Readout Circuits for CMOS Image Sensors" by Xiaoliang Ge and Albert J. P. Theuwissen.

"In order to address the trade-off between the low input-referred noise and high dynamic range, a Gm-cell-based pixel together with a charge-domain correlated-double sampling (CDS) technique has been proposed to provide a way to efficiently embed a tunable conversion gain along the read-out path. Such readout topology, however, operates in a non-stationery large-signal behavior, and the statistical properties of its temporal noise are a function of time. Conventional noise analysis methods for CMOS image sensors are based on steady-state signal models, and therefore cannot be readily applied for Gm-cell-based pixels. In this paper, we develop analysis models for both thermal noise and flicker noise in Gm-cell-based pixels by employing the time-domain linear analysis approach and the non-stationary noise analysis theory, which help to quantitatively evaluate the temporal noise characteristic of Gm-cell-based pixels. Both models were numerically computed in MATLAB using design parameters of a prototype chip, and compared with both simulation and experimental results. The good agreement between the theoretical and measurement results verifies the effectiveness of the proposed noise analysis models."

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Espros February newsletter (not on the web site yet) explains the company plans to expand its BSI production line:

"One of the most important factors is time to market. The semiconductor industry is in a very difficult position in this respect because the supply chain and thus the lead time is quite long.

Typically, more than 20 weeks from the start of wafer processing to final chips is not abnormal. Thus, if a shortage in the supply chain occurs, e.g. due to increasing demand, allocation for 30-50 weeks is not really special. In the case of our products where we do rather complex backside processing, we had to add another 11 weeks to the supply lead time one year ago. This situation was not satisfying at all and we decided to invest heavily into additional in-house capabilities.

The result is now that we can do the backside and the back-end processing of the wafers within days, if needed. We showed this performance in a recent project where lead time from wafer production start until the chips were in the lab was only nine weeks. Not just wafer processing and backside processing, but also assembly including AR coating and band-pass filter bonding."

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IC Insights publishes a report on worlds fab closures. It turns out that CIS market expansion has saved two 300mm fabs from closure:

"Renesas sold its 300mm logic fab to Sony in 2014. Sony repurposed that fab to make image sensors. In 2017, Samsung closed its 300mm Line 11 memory fab in Yongin, South Korea, also repurposing it to manufacture image sensors."

According to other sources, the re-purporsed Samsung fab is located in Hwaseong in Gyeonggi Province and should start CIS manufacturing in 1H 2018.

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AutoSens publishes CSEM Christophe Pache presentation on flash LiDARs with a Q&A session starting at 20:20 time:

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BusinessWire: Renesas announced the R-Car V3H SoC for computer vision and AI processing at industry-leading low power levels, targeting automotive front cameras for use in mass-produced Level 3 (conditional automation) and Level 4 (high automation) autonomous vehicles. The new SoC is optimized for use in stereo front cameras and achieves five times the computer vision performance of its predecessor, the R-Car V3M SoC.

The R-Car V3H algorithms include Dense Optical Flow, Dense Stereo Disparity, and Object Classification. The integrated IP for CNN accelerates deep learning at industry-leading low power levels of only 0.3 watts, achieving more than two times of the deep neural network performance of the R-Car V3M.

Samples of the R-Car V3H SoC will be available from Q4. Mass production is scheduled to begin in Q3, 2019.

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BusinessWire: Teledyne DALSA is expanding its manufacturing capacity given increased demand for the company’s CMOS-based digital X-ray detectors. Teledyne DALSA is a leader in the design and assembly of specialized CMOS X-ray detectors which offer superior lag-free, real-time imaging at both higher resolution and reduced X-ray dose levels.

Teledyne detectors feature proprietary active pixel architecture which offers higher image quality, QE and SNR compared with image intensified charge coupled devices (IICCDs), amorphous silicon (a-Si) or amorphous selenium (a-Se) detectors and even other CMOS-based competitive products.

In order to service its global customer base, Teledyne currently operates X-ray detector manufacturing and assembly locations in the Netherlands, Canada and the US.

“The expansion of the cleanroom facilities in the Netherlands will help us satisfy greater anticipated demand from dental and medical imaging OEMs,” said Robert Mehrabian, Chairman, President and CEO of Teledyne. “In fact, we currently expect that demand for our detectors will more than double by 2020 compared with 2017.”

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South China Morning Post publishes an article about Pixelplus launching "moving image HDR sensors" for the automotive applications.

“HDR technology was developed several years ago on the image signal processing (ISP) level, but the issue with digital artefact persisted. Our solution is an image sensor technology that eliminates artefact because functionality is built inside the image sensor itself,” says SK Lee, president and CEO of Pixelplus. “Our plan is to be among the global top five image sensor providers, especially for the automotive industry based on new camera platforms.”

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PRWeb: LensVector seems to shift its liquid crystal lens efforts away from imaging to light fixtures, possibly a result of appointing a new CEO:

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Imaging Resource publishes a review of Light.co L16 computational camera and the conclusion is quite bad:

"After years of hype and teasers, we finally got our hands on one, and suffice it to say, the image quality and performance leave a lot to desired.

...shooting out in the real world, the L16 is pretty much underwhelming on all fronts."

Fine "detail" crop

Light L16 camera

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Three new LiDAR videos have been published on Youtube today. AutoSens publishes Yole Developpment analyst Pierre Cambou presentation on LiDAR market:

The video is currently taken off-line. Will be re-posted here when it's available again.

Now, a shortened video is re-instated:



Waymo publishes self-driving experience from its imaging systems point of view:



SOSLab shows its "Hybrid Scanning" LiDAR demo:

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AutoSens Detroit conference to be held on May 14-17, 2018 announces it agenda with a rich image sensing content:

Near-Infrared QE Enhancing Technology for Automotive Applications
Boyd Fowler
CTO, OmniVision Technologies, Inc.
• Why is near infrared sensitivity important in automotive machine vision applications ?
• Combining thicker EPI, deep trench isolation and surface scattering to improve quantum efficiency, in CMOS image sensors, while still retaining excellent spatial resolution.
• Improving the performance of CMOS image sensors for in cabin monitoring and external night time imaging.

Challenges, opportunities and deep learning for thermal cameras in ADAS and autonomous vehicle applications
Mike Walters, VP of Product Management for Uncooled Thermal Camerast, FLIR Systems
• Deep learning analytic techniques including full scene segmentation, an AI technique that enables ADAS developers to create full scene classification of every pixel in the thermal image.

The emerging field of free-form optics in cameras, and its use in automotive
Li Han Chan, CEO, DynaOptics

Panel discussion: how many cameras are enough?
Tom Toma, Global Product Manager, Magna Electronics
Sven Fleck, Managing Director, SmartSurv Vision Systems GmbH
Patrick Denny, Senior Expert, Valeo
• OEM design engineer – can we make sensors a cool feature not an ugly bolt-on?
• Retail side – how to make ADAS features sexy?
• Tier 1 – minimal technical requirements
• Outside perspective – learning from an industry where safety sells (B2C market)

A review of relevant existing IQ challenges
Uwe Artmann
CTO/Partner , Image Engineering

Addressing LED flicker
Brian Deegan, Senior Expert - Vision Research Engineer , Valeo Vision Systems
• Definition, root cause and manifestations of LED flicker
• Impact of LED flicker for viewing and machine vision applications
• Initial proposals for test setup and KPIs, as defined by P2020 working group
• Preliminary benchmarking results from a number of cameras

CDP – contrast detection probability
Marc Geese, System Architect for Optical Capturing Systems, Robert Bosch

Moving from legacy LiDAR to Next Generation iDAR
Barry Behnken, VP of Engineering, AEye
• How can OEMs and Tier 1s leverage iDAR to not just capture a scene, but to dynamically perceive it?
• Learn how iDAR optimizes data collection, allowing for situational configurability at the hardware level that enables the system to emulate legacy systems, define regions of interest, focus on threat detection and/or be programmed for variable environments.
• Learn how this type of configurability will optimize data collection, reduce bandwidth, improve vision perception and intelligence, and speed up motion planning for autonomous vehicles.

Enhanced Time-Of-Flight – a CMOS full solution for automotive LIDAR
Nadav Haas, Product Manager, Newsight Imaging
• The need for a real 3D solid state lidar solution to overcome challenges associated with lidar.
• Enabling very wide dynamic range by means of standard processing tools, to amplify very weak signals to achieve high SNR and accurately detect objects with high resolution at long range.
• Eliminating blinding by mitigating or blocking background sunlight, random light from sources in other cars, and secondary reflections.
• Enabling very precise timing of the transmitted and received pulses, essential to obtain the desired overall performance.

Panel discussion: do we have a lidar bubble?
Abhay Rai, Director Product Marketing: Automotive Imaging, Sony Electronics
• Do we even need lidar in AV?
• Which is the right combo; lidar + cornering radar or no lidar just radar + camera?
• How many sensors are the minimum for autonomous driving
• Are image sensors and cameras fit for autonomous driving?

All-weather vision for automotive safety: which spectral band?
Emmanuel Bercier, Project Manager, AWARE Project
• The AWARE (All Weather All Roads Enhanced vision) French public funded project is aiming at the development of a low-cost sensor fitting to automotive requirements, and enabling a vision in all poor visibility conditions.
• Evaluation of the relevance of four different spectral bands: Visible RGB, Visible RGB Near-Infrared (NIR) extended, Short-Wave Infrared (SWIR) and Long-Wave Infrared (LWIR).
• Outcome of two test campaigns in outdoor natural conditions and in artificial fog tunnel, with four cameras recording simultaneously.
• Presentation of the detailed results of this comparative study, focusing on pedestrians, vehicles, traffic signs and lanes detection.

Automotive Sensor Design Enablement; a discussion of multiple design enablement tools/IP to achieve smart Lidar
Ian Dennison, Senior Group Director R&D, Cadence Design Systems
• Demands of advanced automotive sensors, driving design of silicon photonics, MEMS, uW/RF, advanced node SoC, and advanced SiP.
• Examining design enablement requirements for automotive sensors that utilize advanced design fabrics, and their integration.

Role of Specialty Analog Foundry in Enabling Advanced Driver Assistance Systems (ADAS) and Autonomous Driving
Amol Kalburge, Head of the Automotive Program , TowerJazz
• Driving improvements in device level figures of merit to meet the technical requirements of key ADAS sensors such as automotive radar, LiDAR and camera systems.
• Optimizing the Rdson vs breakdown voltage to enable higher bus voltages of the future hybrid/EV systems.
• Presenting an overview of advanced design enablement and design services capabilities required for designers to build robust products: design it once, design it right.

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PMD and Infineon present what the call the smallest ToF camera:

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GlobeNewswire: Himax presents Android smartphone samples equipped with its 3D sensing total solution with face recognition capability. The solution is now ready for mass production.

SLiM, Himax’s structured light based 3D sensing total solution which the Company jointly announced with Qualcomm last August, brings together Qualcomm’s 3D algorithm with Himax’s design and manufacturing capabilities in optics and NIR sensors as well as know-how in 3D sensing system integration. The Qualcomm/Himax solution is claimed to be by far the best performing 3D sensing and face recognition total solution available for the Android smartphone market right now.

The key features of the Himax SLiMTM 3D sensing total solution include:

• Dot projector: More than 33,000 invisible dots, the highest in the industry, projected onto object to build the most sophisticated 3D depth map among all structured light solutions
• Depth map accuracy: Error rate of < 1% within the entire operation range of 20cm-100cm
• Face recognition: Enabled by the most sophisticated 3D depth data to build unique facial map that can be used for instant unlock and secure online payment
• Indoor/outdoor sensitivity: Superior sensing capability even under total darkness or bright sunlight
• Eye safety: Certified for IEC 60825 Class 1, the international laser product standard which governs laser product safety under all conditions of normal use with naked eyes
• Glass broken detection: Patented glass broken detection mechanism in the dot projector whereby laser is shut down instantaneously in the event of broken glass in the projector
• Power consumption: Less than 400mW for projector, sensor and depth decoding combined, making it the lowest power consuming 3D sensing device by far among all structured light solutions
• Module size: the smallest structured light solution in the market, ideal for embedded and mobile device integration

“3D sensing is among the most significant new features for smartphone. We are pleased to announce that our SLiM total solution is now ready for mass production. It outperforms all the peers targeting Android market in each and all aspects of engineering. We are working with multiple tier-1 Android smartphone makers, on target to launch 3D sensing on their premium smartphones starting the first half of 2018,” said Jordan Wu, President and CEO of Himax.

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PRNewswire: Mediatek flagship P60 application processor features triple ISP and AI processor:

"Compared to the previous Helio P series, MediaTek Helio P60's three image signal processors (ISPs) increase power efficiency by using 18 percent less power for dual-cameras set-ups. By combining the Helio P60's incredible camera technology with its powerful Mobile APU, users can enjoy AI-infused experiences in apps with real-time beautification, novel, real-time overlays, AR/MR acceleration, enhancements to photography, real-time video previews and more."

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