Photon Counting History

Edward Fisher from the University of Edinburgh, UK publishes "Principles and Early Historical Development of Silicon Avalanche and Geiger-Mode Photodiodes" chapter in an open source "Photon Counting" book.

The chapter is a historical literature review for the development of solid-state photodetection and avalanche multiplication between 1900 and 1969 based on 110+ primary sources that are key in the field over that time.

The author is looking to fill some of the gaps for a later Springer book covering 1900 to 1999, i.e. 100 years of solid-state photodetection with a distinct avalanche focus (with significantly more detail). Edward Fisher is looking for any key papers or patents the readers of this blog think should be included for the 1900-1969 period.

When the full 1900-1999 analysis is finished, Edward aims for it to be the de-facto literature reference for the field, as it is often difficult for busy technical researchers to either find or read some of the older literature.

"The historical development of technology can inform future innovation, and while theses and review articles attempt to set technologies and methods in context, few can discuss the historical background of a scientific paradigm. In this chapter, the nature of the photon is discussed along with what physical mechanisms allow detection of single-photons using solid-state semiconductor-based technologies. By restricting the scope of this chapter to near-infrared, visible and near-ultraviolet detection we can focus upon the internal photoelectric effect. Likewise, by concentrating on single-photon semiconductor detectors, we can focus upon the carrier-multiplication gain that has allowed sensitivity to approach the single-photon level. This chapter and the references herein aim to provide a historical account and full literature review of key, early developments in the history of photodiodes (PDs), avalanche photodiodes (APDs), single-photon avalanche diodes (SPADs), other Geiger-mode avalanche photodiodes (GM-APDs) and silicon photo-multipliers (Si-PMs).

As there are overlaps with the historical development of the transistor (1940s), we find that development of the p-n junction and the observation of noise from distinct crystal lattice or doping imperfections – called “microplasmas” – were catalysts for innovation. The study of microplasmas, and later dedicated structures acting as known-area, uniform-breakdown artificial microplasmas, allowed the avalanche gain mechanism to be observed, studied and utilised."

Holst Centre and Imec Present Organic Fingerprint Sensor

Charbax publishes a video demo of Imec and Holst Centre organic image sensor:

Pico Presents Zense ToF Camera

NotebookItalia: China-based Pico presents Zense camera, its first foray into ToF sensing. The depth processing is based on Rockchip RV1108 with CEVA XM4 vision IP core:

Yole Forecast on 3D Sensing Market

Yole Developpement publishes "3D Imaging & Sensing 2018" report:

"Apple set the standard for technology and use-case for 3D sensing in consumer. From our initial depiction of the market in March 2017, the main gap is in illumination ASP, which is greater than expected. High expenses in dot and flood illumination VCSELs from Lumentum/II-VI/Finisar, along with the dot illuminator optical assembly from ams, are the biggest technology surprises powering Apple’s $1,000 [iPhone X] smartphone.

Yole Développement (Yole) expects the global 3D imaging & sensing market to expand from $2.1B in 2017 to $18.5B in 2023, at a 44% CAGR. Along with consumer, automotive, industrial, and other high-end markets will also experience a double-digit growth pattern.

The transition from imaging to sensing is happening before our eyes. Despite half-successful attempts like Xbox’s Kinect technology and Leap-Motion hand controllers, 3D sensing is now tracking towards ubiquitousness.

Oppo made the first announcement beginning of the year with Orbeec, while Xiaomi released the Mi 8 explorer edition with Mantis as a technology partner. We expect Huawei to release its own solution soon, probably partnering with ams and Sunny Optical.

...players like Himax are currently paying the price for a lower-performance offering and are struggling to get design-ins beyond AR/VR headsets for Microsoft.

Unlike previous sensing components, the responsibility of system design does not fall on the OEM - instead, a specialist is required, such as the Primesense team that Apple acquired in 2013, or other firms like Mantis, Orbbec, and ams, which want play the “specialist” role in the new 3D imaging & sensing ecosystem. Such players orchestrate the final solution while allowing room for the best in each sub-component category.

Is 3D imaging & sensing now ripe for disruption? Yole expects it will take at least 2 -3 years before any new solution start dramatically lowering total system cost."

Smithers Report on Technology Challenges for Image Sensors in ADAS & Autonomous Vehicle

Smithers Apex publishes a report "Technology Challenges for Image Sensors in ADAS & Autonomous Vehicle Markets to 2023." Few quotes:

"...as vehicles approach full autonomy, the need for human-friendly colour reproduction becomes redundant, and the quality requirements on the image sensing for computer vision will increase further. A high dynamic range of 140 dB, resolutions of 8 MP for mono vision and at least 2MP for stereo vision cameras, frame rates beyond 60 fps, a sensitivity of several thousand electrons per lux and second are requested.

At the same time the noise performance should ensure a signal to noise ratio of 1 at 1 millilux, and an exposure time of less than 1/30 s. High dynamic range shall be achieved by as few as possible exposures to minimise motion blur. The compensation of the flickering of LED traffic signs and lights as described in the previous section is even more important for level 4 and 5 vehicles."

SWIR Startup Trieye Raises $3m of Seed Money

Globes: Israeli startup TriEye announces the completion of a $3m seed round led by Grove Ventures. TriEye develops SWIR sensors providing autonomous cars heightened visual capabilities in restricted visual conditions at significantly reduced cost. The technology is based on many years of research at the Hebrew University of Jerusalem by Prof. Uriel Levy.

TriEye cofounder and CEO Avi Bakal says, "The company is offering capabilities that in the past were only accessible to defense and aerospace industries and at a minimal cost compared with the past. This capability improves the safety of advanced driver-assistance systems and is a major step forward to the extensive adoption of the technology by the carmakers."

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.

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."