Thursday, June 21, 2018

AutoSens Brussels Agenda

Autosens Brussels to be held in September 2018 announces its preliminary speakers list. There is quite a lot of image sensors presentations:
  • Introduction to the world of Time-of-Flight for 3D imaging, Albert Theuwissen, Harvest Imaging (Tutorial)
  • Do we have a lidar bubble? Panel discussion
  • Vehicle perception of humans – what level of image quality is needed to recognise behavioural intentions, Panel discussion
  • A review of the latest research in photonics-sensor technologies in automotive, Michael Watts, Analog Photonics
  • Automotive HDR imaging – the history and future, Mario Heid, Omnivision
  • Self-driving cars and lidar, Simon Verghese, Waymo
  • Tier 1 achievements with solid state lidar, Filip Geuens, Xenomatix
  • An Approach to realize “Safety Cocoon”, Yuichi Motohashi, Sony
  • How AI/Computer Vision affects camera design and SOC design, Marco Jacobs, videantis
  • Objective and Application Oriented Characterisation of Image Sensors with EMVA’s 1288 Standard, Bernd Jaehne, EMVA 1288 Chair
  • Review of IEEE P2020 developments, Patrick Denny, Valeo

Xintec Unable to Fill 12-inch WLP Line

Digitimes reports that Xintec has hard time recovering from the loss of its major investor and customer Omnivision. The company has decided to suspend its 12-inch WLP production line for a year due to disappointing demand for mass-market applications. The 12-inch line workforce will be transferred to 8-inch lines to improve revenue and profit.

Wednesday, June 20, 2018

Tunable Plasmonic Filters Enable Time-Sequential Color Imaging

ACS Photonics paper "Tunable Multispectral Color Sensor with Plasmonic Reflector" by Vladislav Jovanov, Helmut Stiebig, and Dietmar Knipp from Jacobs University Bremen and Institute of Photovoltaics Jülich, Germany proposes plasmonic reflectors for color imaging:

"Vertically integrated color sensors with plasmonic reflectors are realized. The complete color information is detected at each color pixel of the sensor array without using optical filters. The spectral responsivity of the sensor is tuned by the applied electric bias and the design of the plasmonic reflector. By introducing an interlayer between the lossy metal back reflector and the sensor, the reflectivity can be modified over a wide spectral range. The detection principle is demonstrated for a silicon thin film detector prepared on a textured silver back reflector. The sensor can be used for RGB color detection replacing conventional color sensors with optical filters. Combining detectors with different spectral reflectivity of the back reflector allows for the realization of multispectral color sensors covering the visible and the near-infrared spectral range.

To our knowledge for the first time a sensor is presented that combines a spatial color multiplexing scheme (side-by-side arrangement of the individual color channels) used by conventional color sensors with the time multiplexing scheme (sequential read-out of colors) of a vertically integrated sensor.
"

Daqri on Importance of Latency in AR/VR Imaging

Daqri Chief Scientist Daniel Wagner publishes an article "Motion to Photon Latency in AR and VR applications:"


Daqri tells about its latency optimization achievements: "Overall, what is the final latency we can achieve with such a system? The answer is: It depends. If we consider rendering using the latest 6DOF pose estimates as the last step in our pipeline that produces fully correct augmentations then achieving a latency of ~17ms is our best-case scenario.

However, late warping can correct most noticeable artefacts, so it makes sense to treat it as valid part of the pipeline. Without using forward prediction for late warping, we can achieve a physical latency of 4 milliseconds per color channel in our example system. However, 4 milliseconds is such a short length of time, making forward prediction almost perfect and pushing perceived latency towards zero. Further, we could actually predict beyond 4ms into the future to achieve a negative perceived latency. However, negative latency is just as unpleasant as positive latency, so this would not make sense for our scenario.
"

Velodyne Lidar 101

Velodyne publishes a promotional video explaining its technology:

Tuesday, June 19, 2018

Lucid Demos Sony Polarization Sensor

LUCID Vision Labs demos Sony IMX250MYR polarized color sensor in its Phoenix camera family. The 5 MP GS sensor with 3.45µm pixel and frame rates of up to 24 fps is based on the popular IMX250 Sony Pregius CMOS color sensor with polarizing filters added to the pixel. The sensor has four different directional polarizing filters (0°, 90°, 45°, and 135°) on every four pixels:

Panasonic Develops 250m-Range APD-based ToF Sensor

Panasonic has developed a TOF image sensorthat uses avalanche PD (APD) pixels and is capable of capturing range imaging of objects up to 250m even at night with poor visibility (there is no mention what is the range in mid-day sunlight). The new sensor applications include automotive range imaging and wide-area surveillance in the dark.

The ToF pixel includes an APD and an in-pixel circuit that integrates weak input signals to enables the 3D range imaging 250 m ahead. The sensor resolution is said to be the world's highest 250,000 pixels for a sensor based on electron-multiplying pixels. This high integration is achieved through the lamination of the electron multiplier and the electron storage as well as the area reduction of APD pixels.

The key innovative technologies are:
  • The area of APD pixels is significantly reduced while the multiplication performance is maintained through the lamination of the multiplier that amplifies photoelectrons and the electron storage that retains electrons.
    The APD multiplication factor is 10,000.
  • Long-range measurement imaging technology

Trioptics Active Alignment, Assembly and Testing of Camera Modules

Germany-based Trioptics demos Procam, its modular manufacturing line for active alignment, assembly and testing of camera modules in mass production:

Fiat-Chrysler Autonomous Car Relies on 5 LiDARs and 8 Cameras

Fiat-Chrysler 5-year plan presentation shows its Level 4 autonomous car with 5 LiDARs and 8 cameras. Most of the LiDARs are defined as "mid-range" possibly meaning their range is shorter than 200m for a cheaper price:

Monday, June 18, 2018

Gil Amelio on Patent Infrigements

Investors Business Daily publishes Gil Amelio article with a story of Pictos vs Samsung lawsuit:

"A typical small inventive company, Pictos Technologies, was put out of business after Samsung aggressively infringed its intellectual property.

Pictos invented an inexpensive image sensor that could be used in countless applications such as mobile phones and automobile cameras, to name only two. This next-generation Image Sensor was a follow-on to my dozen or so image-sensing patents that helped launch the solid-state image-sensor business years earlier. The Pictos technology, developed after years of investment and design, was protected by a portfolio of patents obtained at substantial cost.

In 2014, Pictos sued Samsung in federal court, alleging that it had "willfully infringed" its intellectual property. After years of costly litigation, the case went to trial, where Pictos lawyers introduced evidence that proved Samsung began as a Pictos customer, secretly copied its engineering designs and production process, and replicated them in Korea. Using our technology and its sizable scale, it went on to dominate this sector of the world electronics market.

Following lengthy litigation, the jury ruled in our favor and awarded substantial damages. The judge then trebled the damages based on "evidence of (Samsung's) conduct at the time of the accused infringement." Please note: Samsung's behavior was so egregious that the judge tripled the jury determination of the infringement costs to us.

That was just the first round, though. The verdict can be overturned on appeal, which, of course, Samsung has filed.
"

Update: Once we are at historical stuff, SemiWiki publishes Mentor Graphics CEO Wally Rhines memories from the early days of CCD and DRAM imagers in Stanford University in 1960s.