‘SixthSense’ is a wearable gestural interface that augments the physical world around us with digital information and lets us use natural hand gestures to interact with that information. By using a camera and a tiny projector mounted in a pendant like wearable device, ‘SixthSense’ sees what you see and visually augments any surfaces or objects we are interacting with. It projects information onto surfaces, walls, and physical objects around us, and lets us interact with the projected information through natural hand gestures, arm movements, or our interaction with the object itself. ‘SixthSense’ attempts to free information from its confines by seamlessly integrating it with reality, and thus making the entire world your computer.

References
[1] http://fluid.media.mit.edu/projects.php?action=details&id=68

The newest computer vision technology can’t literally see through your sweater and slacks, but it can determine the shape of your unclad body.

Brown University computer scientists have developed software that takes ordinary images of people dressed in street clothes and digitally peels away the layers to determine their 3-D body shape.

In a partnership with Rhode Island State Police, Brown computer scientist Michael Black developed tools to figure out a person’s basic physical attributes from a grainy surveillance video.

[1] Boston News, Science Article.

In this “Sneakey” Computer Vision project, features of the key is extracted from the photograph and accordingly a duplicate of the key is produced. Most importantly, photos can be taken even 200 feet away from keys without the owners knowledge.

So it is time to blur out the your keys in the photograph, like you did for number plates, credit card numbers before publishing to facebook, flickr etc. )

For more information have a look at here

The book includes:

• A thorough introduction to OpenCV
• Getting input from cameras
• Transforming images
• Shape matching
• Pattern recognition, including face detection
• Segmenting images
• Tracking and motion in 2 and 3 dimensions
• Machine learning algorithms

[1] Learning OpenCV Book at Safari
[2] OpenCV Library

Artificial Eyeball

Extracted from the Article:
Mimicking the curves of a human retina has enabled a digital image sensor to take wide-angle pictures without distortion. This is possible thanks to an improved method of transferring silicon sensors onto a curved surface.

They built their hemispherical electronic eye by first using conventional photolithography to build silicon photodiodes 500 micrometers square and 1 micrometer thick. These were then wired into a flexible 16-by-16 array using chromium and gold.

Separately, they created a 1-cm-wide hemisphere out of a stretchy plastic, and stretched it into a flat surface. That stretched surface, or “drumhead”, was then pressed against the photodiode array.

The silicon squares stuck to the stretched plastic thanks to van der Waals forces, which was then allowed to spring back to its original hemispherical shape. As the array took its new form, the photodiodes packed together tightly and the connecting wires arced away from the surface, but the array was undamaged.

The reformed array was then glued to a curved glass surface, and a conventional lens attached. It now resembled a human eye in construction, with light entering the lens from the front, and passing to the curved “retina” containing the matrix of photodiodes behind.

[1] http://technology.newscientist.com/article/dn14477

Pillow Talk: A computer vision system enables couples to ‘touch’ each other while living far apart
More info found here