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Scottish Microelectronics Centre West Mains Road
Odos Imaging is a technology and manufacturing company specializing in the development and manufacture of advanced cameras for industrial and scientific sectors.
Core technologies are targeted on 3D time-of-flight and freeze motion applications. The uni...
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(31 Total References)
Chris Yates - ...
Chris Yates - CEO
Chris co-founded Odos Imaging with Bob Pettigrew in late 2010, having been recruited by the Siemens Technology Accelerator to help commercialize novel time-of-flight technology.
An experienced industrial technologist, Chris specialises in taking early stage technology through development to commercial products.
Chris was previously the Chief Scientist at Edinburgh based start-up MicroEmissive Displays, which floated on the AIM, London.
He has held positions at Scottish start-up Forth Dimension Displays, as well as being involved in spin-out activities at the University of St Andrews and the Technische Universitat, Berlin.
He has over twenty scientific publications, several patents, and holds a 1st class degree and Ph.D. from Imperial College London.
When not attending to Odos business, Chris
can often be found running around Edinburgh
in practice for the annual marathon or being walked at the beach by his
newly acquired dog, Daisy the cocker spaniel.
is also an enthusiast of all forms of patisserie, and has been known to claim that his
homemade lemon tart represents the pinnacle of the craft.
is unable to reverse park a car, either with or without assistance.
CEO & ...
CEO & Co-founder
will present his
answer to the frequently upcoming question: Is 3D Time-of-Flight imaging technology ready for machine vision applications?
Chris Yates is the CEO and co-founder of Odos Imaging, having been recruited in 2010 to lead the commercialization of novel time-of-flight technology, originally developed within Siemens, Munich.
Since the company was founded the scope and interest in time-of-flight imaging has increased dramatically, and within his
will address the topic predominately from a machine vision perspective.
Photo Chris Yates
An experienced industrial technologist, Chris has specialised throughout his career in taking early stage technology through development to commercial products, and maintains an active interest in research within the field of electro-optics.
Chris was previously the Chief Scientist at Edinburgh based start-up MicroEmissive Displays, a spin-out from Edinburgh University which focused on the development OLED-on-silicon micro-displays for virtual reality applications, and subsequently floated on the AIM, London.
He has held positions at Scottish start-up Forth Dimension Displays working on ferroelectric liquid crystal displays, as well as being involved in various technology spin-out activities at the University of St Andrews, Strathclyde University, as well as the Technische Universität, Berlin.
He has authored over twenty scientific publications, multiple patents, and holds a 1st class degree and Ph.D. from Imperial College, London.
June/July 2014 - Imaging and Machine Vision Europe
CEO, Odos Imaging
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Features about 'Q' - Imaging and Machine Vision Europe
CEO, Odos Imaging
The view that atypical industries are ...
The view that atypical industries are becoming increasingly important for machine vision was seconded by Chris Yates, CEO of Odos Imaging.
He told the press conference: 'Non-traditional applications are providing strong growth in the machine vision sector, often requiring solutions in complex and ill-constrained environments, for example the automated measurement and harvesting of crops in the field or greenhouse.'
was announced as the winner of the Vision Award 2014 in the evening of 4 November for its time-of-flight 3D imaging system, Real.iZ VZ-1000.
said that high-resolution 3D imaging offered particular benefits to applications that are away from the factory.
said that such applications often have to tolerate high levels of ambient light while delivering a high-resolution image to identify specific features.
also predicted that combination imagery, such as hyper-spectral and range information from the same system, would increase the scope of application for machine vision techniques.