Imagine yourself at lunch hour in a hawker center, sometime in the near future. You see a diner with an appetizing food item. Rather than ask the diner about it, you decide to use your Google Glasses to take a snapshot of the food item, and then send it over to Graymatics’ cloud based cognitive media processing servers.
In a few milliseconds, Graymatics comes back to you and shows the results on the heads-up display of your Google Glasses. The food item is a new variety of Pineapple Chicken rice mixed with coriander sauce. Combined with data from HungryGoWhere, you find that it can be bought at Lian’s Food Stall located a just few meters away. You also see the latest reviews from past diners about the chicken rice.
The hawker center scenario above is but one of the promising use cases that Graymatics cognitive media processing can bring to life. The technology consists of algorithms that can instantly recognize and categorize image and video content that is fed to it. It can then tell users what the contents are about and who or what is in them.
Praveen Kakar and Sonal Chowdhary, Graymatics’ system engineer and business development executive respectively, told me that the system can achieve 90% accuracy. They point to their success in recognition fashion apparels. Apparently this is a highly difficult thing to do in this field of image processing.
Whoever can crack this could have a lucrative business on their hands. Graymatics is one of many innovators giving it a go. In a recent seminar at IDA for Cloud Call 6 in Singapore, I saw local universities NTU and NUS (check out Jiku) roll out similar technology. Google is also pursuing image processing with their Artificial Brain project, which managed to recognize cats and humans on its own after thousands of YouTube video were fed to it.
But Graymatics, headquartered in Santa Clara with a presence in Singapore, is on the verge of commercializing their solutions. It has already made demonstrations at the recent Techventure 2012, and is undergoing client test trials and pilot projects. Using this base technology, they have four services to offer: Image Assurance, Context Connect, TubeScan and Interest Insights.
The first two are related to imagery. Image Assurance, which is near real-time, is a filtering system that can detect nudity, violence, or content related to drug abuse. Online publications can use it to detect offensive advertisements and prevent them from showing.
Context Connect, which processes a picture every few seconds, helps publishers place relevant ads within images and videos, by matching the ad to the content.
TubeScan and Interest Insights relate to video. TubeScan is like Context Connect: it extracts metadata from the content to be returned to the publisher, who can take the information and monetize it. Interest Insights, meanwhile, allows publisher to take the meta data and use it to build viewer profiles.
There are limits to what the technology can achieve now. The process of using their API (as of publishing time) is mostly manual. Any publisher wishing to monetize their video will have to sign up, get the API, point the Graymatics servers to the URL to be crawled, wait for the servers’ algorithm to compute and process the images or video, then wait to get the metadata back.
|Graymatics CEO and President Abhijit Shanbhag has disputed the article’s claim that implementing Graymatics is “mostly manual”. He says: “The publisher places one line of Graymatics’ Java script code on their web-site (taking a few seconds) and that’s it… the contextual ads just appear on side of the video from Graymatics’ or third party product feeds.”|
This metadata will contain the time code in the video that is ‘interesting’, together with items of interests, like ‘food’, ‘eyewear’, ‘pants’, ‘dress’ etcetera. You, as the publisher, would then need to take this result and manually embed the items you want to sell onto the video.
It is still a lot of work for publishers to engage Graymatics’ solutions, at least for the ecommerce purposes. Granted, there are other potential uses for the technology that might not require so much ‘integration’ work for publishers and content owners—security, polling applications, mood recognition, and so on.
While this cognitive media technology has huge potential, the company must make it easier for publishers to integrate these into their properties. One way of doing it would be to use an API to call up Graymatics’ servers and then have Graymatics do the embedding and interfacing with a pool of advertisers’ product offerings.
Competitors could use this blindspot to offer a more compelling product than Graymatics. They could also use crowd sourcing (like Google and Amazon Turk) instead of computer algorithms to identify the same things that Graymatics does — maybe at a even higher accuracy rate. They could offer freebies to the volunteers that come from advertisers whose products are successfully identified in images and videos.
This competitor would then store the information about the image or video on a database and offer that as an API to the publishers for later use. Their end product could be a client app that presents the content with the embedded ad. Revenue share might be one option to make money for both the publisher, advertiser and the intermediary.
But then again, Graymatics is just starting up. Maybe in a few months’ time, we would see more refinements on the business model front.
More Info on Graymatics:
Headquarters is at: 4555 Great America Parkway, 3rd Floor Santa Clara, CA 95054, United States with their Asia Pacific branch at 3 Science Park Drive, 2nd Floor , Singapore 118223. Key Officers include: Dr Abhijit Shanbhag (President and CEO), Dr Bernard Widrow (Chief Scientist) and Perry Oza (CFO). Citrix Startup Accelerator provide the seed funding in June 30, 2011 (Note: The article earlier stated that Citrix invested in Graymatics in June 2012 and that the CFO was Meenakshi Singh. Both are incorrect. Meenakshi was replaced by Perry 15 months ago).
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