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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 News Research & Development

Pittsburgh Pattern Recognition

On July 22 2011, Google acquired PittPatt, the Pittsburgh Pattern Recognition Team, a privately-held spin out of CMU Robotics.

Three questions jumped out when I learned of this acquisition.

  • Why? Doesn't Google already have face recognition technology?
    Unfortunately, based on the publicly available information, it's not clear what is new or different about PittPatt's technology. Okay, so they have an SDK. There are several possible explanations for this acquisition. Maybe the previous facial recognition technology Google had acquired with Neven Vision in August 2006 then released as part of Picasa in 3rd quarter 2008 (it appeared in Picasa as early as May 2007) was insufficient. Insufficient could mean inaccurate too often, too difficult to implement in mobile, not scalable. That doesn't seem likely.
    Maybe the difference is that the PittPatt technology was working on video as well as still images. YouTube already has a face recognition algorithm, but it is not real time. For AR it would be valuable if the face recognition and tracking performs reliably in real time.
    Another possible explanation has to do with IP. Given the people who founded PittPatt, perhaps there are some intellectual properties that Google wants for itself or to which it wants to prevent a competitor to have access.
     
  • What are the hot "nearby" properties that will get a boost in their valuation as a result of Google's purchase?
    Faces are the most important attribute we have as individuals and the human brain is hard wired to search for and identify faces. Simulating what our brains do with and for faces is a fundamental computer vision challenge. Since this is not trivial and so many applications could be powered by face recognition (and when algorithms can recognize faces, other 3D objects will not be far behind), there's always a lot of resources going into developing robust, accurate algorithms.

     

     

    Many–perhaps dozens–of commercial and academic groups continually work on facial recognition and tracking technology. Someone has certainly done the landscape analysis on this topic. One of the face recognition research groups with which I've had contact is at Idiap in Martigny, Switzerland. Led by Sebastien Marcel, this research team is focusing on the use of such highly accurate facial recognition that it can be the basis for granting access. KeyLemon is an Idiap spin off using the Idiap technology for biometric authentication to personal computers. And, there is (almost certainly) a sizable group already in Google dedicated to this topic. 
     

  • What value added services or features can emerge that are not in conflict with Google's privacy policy and haven't been thought of already/implemented by Google and others?
    This is an important question that probably has a very long and complex, multi-part answer. I suspect it has a lot to do with 3D objects. What's great about studying faces is that there are so many different ones to work with and they are plastic (distort easily). When the algorithms for detecting, recognizing and tracking faces in video are available on mobile devices, we can imagine that other naturally occurring and plastic objects would not be too far behind.

I hope Eric Schmidt is proven wrong about there not being facial recognition in the future of Google Goggles and similar applications and we see what is behind the curtain in the PittPatt acquisition!