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Augmented Reality News

Intel’s First Full Acquisition of Korean Firm, Olaworks

The Korea Herald is not where I normally get my news. Nor do I regularly visit The Register (whose tag line is "Biting the Hand that Feeds IT"). But today I visited both in order to learn more about Intel's $30.7M acquisition of Olaworks.

In case you are not familiar with it, Olaworks was one of the early companies to dedicate itself first to computer vision (primarily face recognition) and then to apply its intellectual property to solve Augmented Reality challenges. The founder of Olaworks, Dr. Ryu Jung-hee, has been a long-standing friend and colleague and one of the most outgoing Koreans I've met. Ryu has attended at least four out of the past five AR Standards Community meetings and miraculously shows up at other events (e.g., he accepted my invitation to come to the first Mobile Monday Beijing meeting and showcase on the topic of mobile AR, and presented about Olaworks during the first AR in China meeting, one year ago).

Not only am I pleased for Ryu and the 60 employees who work for Olaworks, I'm also impressed that an analyst concluded that one reason for the acquisition might be Olawork's facial recognition technologies. At present LG Electronics, Pantech, and HTC make use of Olawork’s face recognition technology in their phones. Gartner analyst Ken Dulaney told The Reg that Intel’s decision to acquire was probably informed by the growing popularity of face recognition software in the consumer space. In fact, Texas Instruments recently shared with me that they are very proud of the facial recognition performance they have on the OMAP. Face recognition could be used for a lot of different applications (not just AR) when it is embedded into the SoC, as an un-named source suggested might be Intel's intention since Olaworks seems to be heading for integration with another Intel acquisition, Silicon Hive.

Another analyst speculating on the acquisition, Bryan Ma of IDC, sees the move as one of many steps Intel is taking to "prove it’s better than market leader ARM in the mobile space. It has been trying to position Medfield as a better performance processor using the same power consumption as ARM,” he told The Reg. “In the spirit of this it would make sense for Intel to move for technology and apps which can harness that horsepower to differentiate it from ARM.”

I'm not familiar with the Korean investment landscape but it may be important that the Private Equity Korea article on the acquisition makes a point about Intel's acquisition of Olaworks being the first full Korean acquisition the chip giant has made. It seems that we rarely hear about Korean startups in the West and I suspect that one reason is that the most common exit strategy of a young Korean company is acquisition by one of the global handset manufacturers (LG Electronics, HTC, or Samsung), or one of the large network operators. It's perfectly logical, not only from a cultural point of view but also because the Korean mobile market is large and has a long history of having its own national telecommunications standards.

After NTT-DoCoMo's launch of its 3G service in October 2001, the second 3G network to go commercially live was SK Telecom in South Korea on the CDMA2000 1xEV-DO technology in January 2002 (10 years ago). By May 2002 the second South Korean 3G network was launched by KTF on EV-DO and thus the Koreans were the first to see competition among 3G operators.

I hope that the Olaworks exit signals the opening of Korean technology silos and an opportunity for other regions of the world to benefit from the advances the Koreans have managed to make in their controlled 3G network environment.

Categories
Augmented Reality Research & Development

ElipseAR-Cloud Image Recognition

There's long been a debate among computer vision experts between those who envisage feature extraction and matching in the network and those who implement it on the device. There are many factors one must consider and trade offs that must be made but in the end everything boils down to cost: what can you gain by where you put the different tasks if the tasks must be done in real time. For many applications, feature extraction is a bottle neck due to lack of computational power. Qualcomm's AR SDK is an example of device-based recognition.

ElipseAR, a startup based in Madrid, Spain, is heavily on the network side of the debate. They are planning to release a set of tools for markerless (feature-based) Augmented Reality and Computer Vision development that will make image matching and tracking, 3D animation rendering, geolocation using the camera view, face recognition easier to integrate into AR applications. Existing AR apps? Future AR apps?

The company's web site clearly makes a distinction between image recognition, image tracking and matching. What's not clear at the moment, because their position differs depending on which page you are reading, is how much of the ElipseAR processing is to happen within the device and how much will be in the network. They also may be confusing "image" with real time video recognition.

At the moment the company says it will offer its tools for commercial use at no charge. The beta program started in early July and is expected to run until the end of 2011.

Tests must be conducted in real world circumstances to measure the merits of the new algorithm and its architecture. It will be compared against not only other network-based image recognizers such as kooaba, but also other SDKs that have been out for much longer such as Qualcomm AR SDK, Qconcept and others. It's difficult to imagine, for example, ElipseAR getting out ahead of String Labs which released their code June 16, 2011.

Even if the reliability of the ElipseAR algorithms and architecture prove to be up to industry benchmarks, there will continue to be latency out of the control of the developer or user in the cellular networks. There have been rumors that the network "effect" can be overcome, but this will never be a universally reliable solution because coverage of mobile networks is and never will be 100%.