Ambarella Inc.: Difference between revisions
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In July 2015 Ambarella acquired [[VisLab]],<ref>{{cite web|url=https://www.ambarella.com/news/79/74/Ambarella-Acquires-VisLab-a-European-Developer-of-Computer-Vision-and-Intelligent-Automotive-Control-Systems|title=Ambarella Acquires VisLab, a European Developer of Computer Vision and Intelligent Automotive Control Systems - Ambarella|website=www.ambarella.com}}</ref> a pioneer in perception systems and autonomous vehicle research founded by Professor [[Alberto Broggi]]. [[VisLab]] has a history of developing computer vision and [[intelligent control]] systems for automotive and commercial applications, including [[Advanced Driver Assistance Systems|ADAS]] and autonomous vehicles. Subsequent generations of Ambarella SoCs incorporated VisLab perception technologies at the hardware level, with the goal of targeting automotive [[OEM]] camera designs across all of [[Automated driving system#Levels of automation according to SAE|SAE’s six levels of driving automation]]<ref>{{cite web|url=https://blog.ansi.org/2018/09/sae-levels-driving-automation-j-3016-2018/|title=SAE Levels of Driving Automation}}</ref> (ranging from fully manual to fully automated or “steering wheel optional”). |
In July 2015 Ambarella acquired [[VisLab]],<ref>{{cite web|url=https://www.ambarella.com/news/79/74/Ambarella-Acquires-VisLab-a-European-Developer-of-Computer-Vision-and-Intelligent-Automotive-Control-Systems|title=Ambarella Acquires VisLab, a European Developer of Computer Vision and Intelligent Automotive Control Systems - Ambarella|website=www.ambarella.com}}</ref> a pioneer in perception systems and autonomous vehicle research founded by Professor [[Alberto Broggi]]. [[VisLab]] has a history of developing computer vision and [[intelligent control]] systems for automotive and commercial applications, including [[Advanced Driver Assistance Systems|ADAS]] and autonomous vehicles. Subsequent generations of Ambarella SoCs incorporated VisLab perception technologies at the hardware level, with the goal of targeting automotive [[OEM]] camera designs across all of [[Automated driving system#Levels of automation according to SAE|SAE’s six levels of driving automation]]<ref>{{cite web|url=https://blog.ansi.org/2018/09/sae-levels-driving-automation-j-3016-2018/|title=SAE Levels of Driving Automation}}</ref> (ranging from fully manual to fully automated or “steering wheel optional”). |
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== Technologies == |
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Ambarella develops intelligent [[embedded systems|embedded processors]] for a range of camera markets—including security, [[wearable technology|wearable]], drone, [[action camera|sports/action]], and automotive—with an emphasis on several core technologies. |
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'''Dedicated Hardware Architecture for Computer Vision''' |
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Known as CVflow®, Ambarella’s computer vision architecture includes a dedicated hardware engine programmed with a high-level algorithm description, allowing [[Convolutional Neural Network|convolutional neural networks (CNNs)]] trained with industry-standard tools (such as [[Caffe (software)|Caffe]] and [[TensorFlow]]) to be mapped onto CVflow-based chips. This approach represents a marked difference from that of general-purpose architectures, such as those offered by [[GPU]]s and [[CPU]]s, which are popular alternatives for computer vision processing. |
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'''Stereovision''' |
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While Ambarella chips are capable of monocular processing, [[Computer stereo vision|stereovision]] is a key focus area for the company. Using cameras with multiple lenses and [[image sensors]], Ambarella’s stereovision processing enables the capture of three-dimensional imagery via the simulation of [[binocular vision]], making it possible to [[Obstacle avoidance|detect generic obstacles]] that a perception system hasn’t been trained to recognize. This generic 3D obstacle detection can be valuable when deployed in partial or fully autonomous robotics applications where atypical objects may be encountered. |
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'''Edge Design''' |
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In contrast to [[Cloud computing|cloud]]-dependent hardware technologies, Ambarella’s technologies are designed for use in [[edge computing|edge]] applications, where a significant share of the processing is performed locally, onboard the device. To meet the demands of processing at the edge, Ambarella products prioritize low power consumption, reduced physical footprint, and extended operating temperature ranges. |
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'''Image Processing''' |
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Ambarella processors include specialized [[digital image processing]] hardware to convert raw image sensor data into color-corrected imagery, removing [[image noise|noise]] to improve quality in various lighting conditions, as well as performing [[lens distortion]] correction, [[Image stabilization#Digital image stabilization|digital image stabilization]], and [[High dynamic range|high dynamic range (HDR)]] processing. |
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The resulting image is either |
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(a.) encoded for streaming (e.g., in a security camera) or saving as a file (e.g., in an action/sports camera), |
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(b.) processed by computer vision algorithms to sense the surrounding environment (e.g., in an automotive front ADAS camera), |
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(d.) presented to the user on a visual display (e.g., in an automotive electronic mirror). |
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'''Video encoding''' |
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Ambarella SoCs use [[data compression]] techniques to encode video streams into popular industry-standard coding formats, including [[H.264]] and [[H.265]]. |
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== Applications == |
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Ambarella processors are designed specifically for automotive, security, consumer (e.g., sports, drone), and industrial/robotics camera applications. |
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'''Automotive''' |
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Ambarella automotive SoCs target both [[automotive aftermarket|aftermarket]] and [[OEM]] camera designs. Relevant applications include simple [[dashcam|drive recorders]] (i.e., dash cams), front [[advanced driver assistance system|ADAS]] cameras, [[Driver Monitoring System|driver and in-cabin monitoring systems]], electronic mirrors, 360° [[surround view]] systems with parking assistance, and stereovision cameras for vehicular autonomy. Key automotive features include [[lane departure warning system|lane departure warning]], [[lane departure warning system|lane keeping]], [[forward collision warning]], auto [[emergency brake assist|emergency braking]] (AEB), intelligent headlight control/high beam assist, speed assist, auto [[Intelligent Parking Assist System|parking assist]] (APA), [[blind spot detection]], target tracking, generic [[object detection|obstacle detection]], [[digital elevation model|terrain modeling]], curb/barrier detection, and [[sensor fusion]]. |
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'''Security''' |
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The company’s professional security and home monitoring camera applications place an emphasis on [[object detection]]/classification ([[Convolutional Neural Network|CNN]]-based), face detection and [[facial recognition system|recognition]], person/pet/vehicle detection, [[automatic number-plate recognition|license plate recognition (ANPR)]], behavioral analysis, and high-resolution image processing in low-light and high-contrast environments. Target camera designs include indoor/outdoor cameras, multi-sensor cameras, [[intelligent transport system|intelligent transport systems (ITS)]] and traffic cameras, [[retail]] cameras, wire-free cameras, and [[smart doorbell|smart video doorbells]]. |
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'''Consumer''' |
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Building on its history in powering [[mass-market]] consumer video devices, Ambarella continues to target [[action camera|sports/action]] cameras, [[virtual reality|VR]] cameras, [[Quadcopters|drones]], and [[wearable technology|wearable]] cameras. Ambarella consumer processors prioritize high-resolution image processing, video compression, low-power operation, and computer vision features such as smart video editing, target-of-interest tracking, and [[augmented reality]]. |
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'''Industrial and Robotics''' |
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Ambarella computer vision processors are designed to enable a variety of intelligent [[robotics]] applications, including [[automated guided vehicles|automated guided vehicles (AGVs)]], consumer robots, and industrial/[[machine vision]] solutions. Key features of interest include [[low-latency]] computer vision performance, [[neural network]] processing, [[Computer stereo vision|stereovision]] capabilities, and high-resolution/high-framerate [[video analysis]]. |
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==Awards and Recognition== |
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* 2009: Global Semiconductor Alliance<ref>{{cite web|url=https://www.gsaglobal.org|title=Global Semiconductor Alliance}}</ref> (GSA) Start-Up to Watch Award |
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* 2010: GSA Most Respected Private Semiconductor Company Award |
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* 2011: GSA Most Respected Private Semiconductor Company Award |
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* 2012: GSA Most Respected Private Semiconductor Company Award |
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* 2013: GSA Analyst Favorite Semiconductor Company Award by Morgan Stanley |
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* 2014: GSA Most Respected Semiconductor Company |
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* 2014: Ambarella is #12 on Forbes Americas's Best Small Companies 2014<ref>{{cite web|url=https://www.forbes.com/companies/ambarella/#439416204f48|title=Ambarella on the Forbes America's Best Small Companies List}}</ref> |
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* 2015: GSA Most Respected Public Semiconductor Company and Best Financially Managed Semiconductor Company Awards for achieving $100M to $500M in annual sales. |
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* 2019: [[Robert Bosch GmbH|Bosch]] Global Supplier Award |
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== See also == |
== See also == |
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== References == |
== References == |
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{{Reflist}} |
{{Reflist}} |
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== External links == |
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* {{Official website|http://www.ambarella.com/}} |
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Revision as of 02:01, 26 January 2022
 | This article contains content that is written like an advertisement. (April 2020) |
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| Company type | Public |
|---|---|
| Nasdaq: AMBA Russell 2000 Component | |
| Industry | Semiconductors |
| Founded | 2004 |
| Headquarters | , |
Key people |
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Number of employees | 750 (2019) |
| Website | ambarella |
Ambarella, Inc. (Nasdaq: AMBA) is a fabless semiconductor design company,[1] focusing on low-power, high-definition (HD) and Ultra HD video compression, image processing, and computer vision processors. Ambarella's products are used in a wide variety of human and computer vision applications, including video security, advanced driver assistance systems (ADAS), electronic mirror, drive recorder, driver and in-cabin monitoring, autonomous driving, and robotics applications. Ambarella's system on chips (SoCs) are designed to deliver a combination of video compression, image processing, and computer vision performance with low-power operation to enable cameras to extract data from high-resolution video streams.
History
Ambarella was founded in 2004 by Feng-Ming (Fermi) Wang and Les Kohn with the goal of developing high-definition H.264 video encoders for the professional broadcast market. Soon after, Ambarella applied this same technology to consumer video and security IP camera markets, focusing on the development of low-power, compression-efficient chips capable of producing high-quality imagery in challenging lighting and high-motion environments. Over the next decade, Ambarella chips were featured in a number of notable consumer camera products, including the GoPro Hero, the Dropcam by Nest, and the DJI Phantom series of drones.
In July 2015 Ambarella acquired VisLab,[2] a pioneer in perception systems and autonomous vehicle research founded by Professor Alberto Broggi. VisLab has a history of developing computer vision and intelligent control systems for automotive and commercial applications, including ADAS and autonomous vehicles. Subsequent generations of Ambarella SoCs incorporated VisLab perception technologies at the hardware level, with the goal of targeting automotive OEM camera designs across all of SAE’s six levels of driving automation[3] (ranging from fully manual to fully automated or “steering wheel optional”).
See also
References
- ^ "AMBARELLA ANNUAL REPORT". Archived from the original on 2017-11-07.
- ^ "Ambarella Acquires VisLab, a European Developer of Computer Vision and Intelligent Automotive Control Systems - Ambarella". www.ambarella.com.
- ^ "SAE Levels of Driving Automation".