Visual Industry Guide
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Yole Developpement report "ALD equipment market surging with 12% CAGR to reach $680M in 2026, penetrating all More-than-Moore applications" states that CIS is by far the largest market for Atomic Layer Deposition systems:
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TheElec: Samsung is to use chip-scale packaging (CSP) to reduce the cost of its low resolution image sensors starting 2022, according to TheElec sources. Currently, Samsung uses chip on board (COB) approach for all sensors.
CSP is done at the wafer level, unlike COB, resulting in increased productivity and lower assembly clean room requirements.
The downside of CSP can only be done in lower resolution image sensors. Most higher resolution image sensors are manufactured with COB. TheElec sources say that CSP can support up to 2MP resolution at as of now.
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Korea-based company Syncron presents its first CIS product - 288MP sensor with 3.5um global shutter pixels. Syncron started a long time ago as a spin-off from Kodak Korea and specializes in high-speed and high-resolution industrial digital cameras. The company has been in machine vision camera distribution business, and the new DCS288M sensor appears to be its first CIS product.
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EETimes: SK Hynix presents A4C quad pixel PDAF technology:
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Harbin Institute of Technology, China, publishes MDPI paper "An Entropy-Based Anti-Noise Method for Reducing Ranging Error in Photon Counting Lidar" by Mingwei Huang, Zijing Zhang, Jiaheng Xie, Jiahuan Li, and Yuan Zhao.
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Heriot-Watt University and University of Glasgow publish Journal of Physics paper "Ge-on-Si single-photon avalanche diode detectors for short-wave infrared wavelengths" by Fiona Thorburn, Xin Yi, Zoe Greener, Jaroslaw Kirkoda, Ross Millar, Laura Huddleston, Douglas J Paul, and Gerald S Buller.
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Universidad Nacional del Sur (Argentina), Fermi Lab (USA) and Tel Aviv University (Israel) publish an Arxiv.org paper "Smart readout of nondestructive image sensors with single-photon sensitivity" by Fernando Chierchie, Guillermo Fernandez Moroni, Leandro Stefanazzi, Eduardo Paolini, Javier Tiffenberg, Juan Estrada, Gustavo Cancelo, and Sho Uemura.
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Facebook-Meta patent application US20210360132 "Stacked Image Sensor with Polarization Sensing Pixel Array" by Manoj Bikumandla, John Enders Robertson, and Andrew Matthew Bardagjy unveils the company's ideas for the sensor for its upcoming AR glasses:
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A&S Magazine: InfiRay (former IRay, Chinese name Rui Chuang Wei Na) subsidiary Arrow presents a surveillance camera featuring world's first 2MP 8um pixel InfiRay microbolometer thermal camera combined with 4MP visible one. The 8um thermal sensor has been first announced in April 2021 and is integrated into a production camera now.
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Counterpoint Research reports that CIS content per smartphone will expand to an average of 4.1. Despite the global components crunch, CIS growth is expected to grow by double digits to reach almost 6bn units in 2021.
“A big driver has been triple-and-above main camera setups, which accounted for two-thirds of all smartphones sold during the first half,” notes Tarun Pathak, Counterpoint’s director of smartphone research. “What’s really interesting is where a lot of that growth is coming from – Africa, Latin America, India and other emerging markets. As we move through post-COVID upgrade cycles, especially in Android heavy markets, we’re seeing OEMs offer increasingly sophisticated camera hardware to their customers across all segments.”
“High-resolution has also been an area of focus, with 48MP-plus becoming standard. Again, we’re seeing emerging markets lead in growth; and 64MP is starting to become a major segment too. High-res is very important for what is the most hotly contested price band globally – the wholesale $100-$399 category. During the second quarter, two-thirds of devices were high-res and we expect further share increases for the full year.”
“If you’re a product manager today delivering a quad cam device, then you’re probably thinking of configuring wide + ultrawide + macro + depth. But the playing field changes quickly, and we’re likely to see macro and ultrawide merge, leaving room for even more options like telephoto or time-of-flight. Increasing choice and complexity is why algorithm development has become such a critical factor in the success of camera systems,” states Ethan Qi, Counterpoint’s lead camera components analyst.
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TalkAndroid, GSMArena: Mediatek presents a 4nm Dimensity 9000 application processor for future smartphones with quite impressive imaging features:
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National University of Singapore and Korea Yonsei University present an ACM paper "LAPD: Hidden Spy Camera Detection using Smartphone Time-of-Flight Sensors" by Sriram Sami, Sean Rui Xiang Tan, Bangjie Sun, and Jun Han and a poster "On Utilizing Smartphone Time-of-Flight Sensors to Detect Hidden Spy Cameras" by the same authors. The detection was tested on Samsung Galaxy S20+, S20 Ultra 5G, and Note 10+ containing VGA Sony IMX516 ToF sensor. Although the sensor has VGA resolution, the current Android API only provides a 240 × 320 image.
"Tiny hidden spy cameras concealed in sensitive locations including hotels and bathrooms are becoming a significant threat worldwide. These hidden cameras are easily purchasable and are extremely difficult to find with the naked eye due to their small form factor. The state-of-the-art solutions that aim to detect these cameras are limited as they require specialized equipment and yield low detection rates. Recent academic works propose to analyze the wireless traffic that hidden cameras generate. These proposals, however, are also limited because they assume wireless video streaming, while only being able to detect the presence of the hidden cameras, and not their locations. To overcome these limitations, we present LAPD, a novel hidden camera detection and localization system that leverages the time-of-flight (ToF) sensor on commodity smartphones. We implement LAPD as a smartphone app that emits laser signals from the ToF sensor, and use computer vision and machine learning techniques to locate the unique reflections from hidden cameras. We evaluate LAPD through comprehensive real-world experiments by recruiting 379 participants and observe that LAPD achieves an 88.9% hidden camera detection rate, while using just the naked eye yields only a 46.0% hidden camera detection rate."
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National University of Singapore and Korea Yonsei University present an ACM paper "LAPD: Hidden Spy Camera Detection using Smartphone Time-of-Flight Sensors" by Sriram Sami, Sean Rui Xiang Tan, Bangjie Sun, and Jun Han and a poster "On Utilizing Smartphone Time-of-Flight Sensors to Detect Hidden Spy Cameras" by the same authors. The detection was tested on Samsung Galaxy S20+, S20 Ultra 5G, and Note 10+ containing VGA Sony IMX516 ToF sensor. Although the sensor has VGA resolution, the current Android API only provides a 240 × 320 image.
"Tiny hidden spy cameras concealed in sensitive locations including hotels and bathrooms are becoming a significant threat worldwide. These hidden cameras are easily purchasable and are extremely difficult to find with the naked eye due to their small form factor. The state-of-the-art solutions that aim to detect these cameras are limited as they require specialized equipment and yield low detection rates. Recent academic works propose to analyze the wireless traffic that hidden cameras generate. These proposals, however, are also limited because they assume wireless video streaming, while only being able to detect the presence of the hidden cameras, and not their locations. To overcome these limitations, we present LAPD, a novel hidden camera detection and localization system that leverages the time-of-flight (ToF) sensor on commodity smartphones. We implement LAPD as a smartphone app that emits laser signals from the ToF sensor, and use computer vision and machine learning techniques to locate the unique reflections from hidden cameras. We evaluate LAPD through comprehensive real-world experiments by recruiting 379 participants and observe that LAPD achieves an 88.9% hidden camera detection rate, while using just the naked eye yields only a 46.0% hidden camera detection rate."
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National University of Singapore and Korea Yonsei University present an ACM paper "LAPD: Hidden Spy Camera Detection using Smartphone Time-of-Flight Sensors" by Sriram Sami, Sean Rui Xiang Tan, Bangjie Sun, and Jun Han and a poster "On Utilizing Smartphone Time-of-Flight Sensors to Detect Hidden Spy Cameras" by the same authors. The detection was tested on Samsung Galaxy S20+, S20 Ultra 5G, and Note 10+ containing VGA Sony IMX516 iToF sensor. Although the sensor has VGA resolution, the current Android API only provides a 240 × 320 image.
"Tiny hidden spy cameras concealed in sensitive locations including hotels and bathrooms are becoming a significant threat worldwide. These hidden cameras are easily purchasable and are extremely difficult to find with the naked eye due to their small form factor. The state-of-the-art solutions that aim to detect these cameras are limited as they require specialized equipment and yield low detection rates. Recent academic works propose to analyze the wireless traffic that hidden cameras generate. These proposals, however, are also limited because they assume wireless video streaming, while only being able to detect the presence of the hidden cameras, and not their locations. To overcome these limitations, we present LAPD, a novel hidden camera detection and localization system that leverages the time-of-flight (ToF) sensor on commodity smartphones. We implement LAPD as a smartphone app that emits laser signals from the ToF sensor, and use computer vision and machine learning techniques to locate the unique reflections from hidden cameras. We evaluate LAPD through comprehensive real-world experiments by recruiting 379 participants and observe that LAPD achieves an 88.9% hidden camera detection rate, while using just the naked eye yields only a 46.0% hidden camera detection rate."
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Univeristat Erlangen-Nurnberg, Germany, publishes Arxiv.org paper "Image Super-Resolution Using T-Tetromino Pixels" by Simon Grosche, Andy Regensky, Jürgen Seiler, André Kaup.
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Université Grenoble Alpes publishes Maxence Bouvie's PhD thesis "Study and design of an energy efficient perception module combining event-based image sensors and spiking neural network with 3D integration technologies."
"Event-driven acquisition permits to generate sparse data, with high acquisition speed at the order of the microsecond, while conserving an exceptionally large dynamic range. Event-driven imagers are thus highly suited for deployment in situations where speed and application robustness are of high importance. However, event-based image sensors come with major drawbacks that render them nearly impracticable in embedded situations. They are noisy, poorly resolved and generate an incredible amount of data relatively to their resolution. This Ph.D. study thus focuses on understanding how they can be used, and how their drawbacks can be alleviated. The work explores bio-inspired applications for tasks where frame-based methods are already successful but present robustness flaws because classical frame-based imagers cannot be intrinsically high speed and high dynamic range. This manuscript provides leads to understand and decide why some algorithms matches more than other to their novel data type. It also tries to touch upon the reasons these sensors cannot be used as they are, but how they could be efficiently integrated into classical frame-based algorithmic pipelines and systems by deploying motion compensation of the raw data. In addition, a bio-inspired hardware-based solution to simultaneously reduce the output bandwidth and filter out noise, directly at the output of a grid of event-based pixels, is presented. It consists in the hardware implementation of a bio-inspired convolutional neural network accelerator - a neuromorphic processor – distributed near-sensor, that takes major advantages from being conceived toward a three-dimensional integration. This system was designed for minimizing its power budget, at the 28nm FDSOI node, and demonstrates a 2.86pJ per synaptic operation – or 93.0aJ per input event per pixel. On top of that, it is scalable for megapixel resolution sensors without induced overhead."
Appendix C (pp. 134-135) gives a nice comparison of Samsung, Prophesee (Sony), and Celepixel (Omnivision) event-driven sensor approaches.
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Teledyne publishes 2 videos: "3D ToF Imaging" and "Clarity at High Speed."Image Sensors World Go to the original article...
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GlobeNewswire: Himax quarterly earning release updates about its WiseEye ultra-low power image sensing solution:
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BusinessWire: OmniVision and Diaspective Vision GmbH announce their partnership in the development of a new type of endoscopic camera, the MALYNA system, which is based on multispectral imaging technology.Image Sensors World Go to the original article...
Infineon investor presentation shows the company's view on ToF market size and its products:
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InterDigital publish a MDPI paper "Optical Efficiency Enhancement of Nanojet-Based Dielectric Double-Material Color Splitters for Image Sensor Applications" by Oksana Shramkova, Valter Drazic, Bobin Varghese, Laurent Blondé, and Valerie Allié.
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Sohu publishes an interview with Deng Jian, CEO of Ruisi Zhixin, english name AlpsenTek, a developer of hybrid of event-driven with regular sensor. Few quotes in Google translation:
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Counterpoint publishes a report on smartphone camera resolution trends:
"Despite supply shortages, smartphone rear cameras are increasingly adopting high-resolution image sensors, which continue to penetrate lower-end smartphone segments. According to the latest research from Counterpoint Smartphone Camera Tracker, smartphones featuring rear main cameras powered by 48MP and above megapixels accounted for 43% of total sales in Q2 2021, rising significantly from 38.7% in Q1 2021. The share of 64MP alone increased 3.5% QoQ to 14% in Q2 2021.
Commenting on this high-resolution advance, Senior Analyst Ethan Qi said, “48MP and 64MP have become the mainstream for models priced between $200 and $400, while flagship smartphones resort to large-area sensors to deliver a DSLR-like professional performance, of which 50MP is the most adopted. Although the share of 108MP fell to 3.1% in Q2 2021, the more affordable 0.7µm-based 108MP sensors continue to spread to mid-range models from OEMs such as Redmi and realme.”
On the other hand, low-resolution sensors continue to suffer from the demand-supply imbalance, with the price increasing sharply. For instance, 5MP sensors have experienced more than a 10% increase in cost since the beginning of this year.
Nevertheless, entry-level smartphones (wholesale price below $100) continue to upgrade their rear primary cameras from 8MP and below resolutions to 12MP or 13MP. Therefore, the collective share of the 8MP and below cameras shrunk to 5.9% in Q2 2021.
In front main cameras, the collective share of 20MP and above resolutions almost stayed flat QoQ in Q2 2021 due to the decline in sales of high-end models. However, we expect the resolution of the front-facing camera to continue to improve with more high-end smartphones adopting 32MP and even 48MP image sensors.
Meanwhile, the share of 8MP and below resolutions further increased to 45.2%, with 5MP and 8MP together accounting for 41.7% on strong demand for low-end smartphones in Q2."
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IEEE Electron Design Society presents 2021 Early Career Award to Gigajon CTO and co-founder Jiaju Ma:
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University of Washington, Seattle, publishes an Arxiv.org paper "Programmable black phosphorus image sensor for broadband optoelectronic edge computing" by Seokhyeong Lee, Ruoming Peng, Changming Wu, and Mo Li.
