Kinect to watch your emotions and serve up ads

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Online adverts are already tailored to your search and browsing history, but now Microsoft has plans to add emotions to the mix. In a recently revealed patent application the company suggests that using its Kinect sensor to analyze your face and body language for emotions could help companies better target their ads. Emotional analysis of emails, search terms and even your online gaming performance could also influence the ads you see.

Just as advertisers currently bid on certain search terms, the patent suggests a company could choose which emotions would match to its adverts. For example, happy people are unlikely to click weight-loss ads, but they might be in the market for a new gadget. Meanwhile, sad people don’t want to hear about club nights and confused people may be looking for a technical support firm to help them out.

Microsoft has previously hinted at using Kinect to bring player’s emotions into games, but perhaps rather than new emotional game mechanics, we’ll soon see ad-supported games that adjust to your mood? The patent suggests that in addition to watching players with Kinect, games could assign emotional states depending on whether you are winning or losing.


Blowfish12@2012 blowfish12.tk Author: Sudharsun. P. R.

Kinect system keeps track of household objects

FITTING your house with a network of Kinect sensors could mean never losing your wallet, TV remote or other small items again.

“We want to make Google for your home,” says Shahriar Nirjon, a computer scientist at the University of Virginia in Charlottesville. To do this, Nirjon and colleague John Stankovic developed Kinsight, which records the location of household items using a Kinect depth camera in each room. It works by tracking people and detecting the size and shape of any objects they interact with. Each object is compared to Kinsight’s database for the house and either recognized or added to the list.

By following the location of objects over time, Kinsight can even distinguish between two identical-looking things – if it records a mug that seems to have jumped from the living room to the kitchen without passing through the space between, for example, it knows it is likely to be two mugs. The system can locate fist-sized objects with an accuracy of 13 centimeters.

Objects need to be manually tagged to be searchable in the system, but Nirjon plans to develop a smartphone app to make this easier. He presented the work at the Distributed Computing in Sensor Systems conference in Hangzhou, China, last month.


Blowfish12@2012 blowfish12.tk Author: Sudharsun. P. R.