MSR User eXperience Technologies (MSR UXT) was previously known as Cambridge Innovation Development (CID).
Our projects range from short single-person tasks to multi-year, multi-person projects. Each team member can own any aspect of a project, including specification, program management, development, test, release management, and technical and/or business relationship management. Relationships include internal and external partners of all levels, ranging from individual contributors to CEO’s.
New Microsoft Garage app uses artificial intelligence to name that breed
Man’s best friend has inspired a new app – Fetch! Using your iPhone camera or photo library, it can identify and classify dogs by breeds and tell you what kind of human personality fits best with specific breeds. And just for fun, the app will even take an informed guess on what kind of dog you or your friends might be.
The team has developed a website, What-Dog.net that has photos you can play with to find out about the breeds, and you can also submit your own photos and share them.
But the app is really where the most progress is apparent. Simply but stylishly designed, it’s incorporated a lot of user feedback from dog owners within the company. It’s full of features, including a scrapbook where you can keep track of all your pictures and results. There’s also an impressive list of breeds that contains information such as disposition, size, coat and what types of families are best suited for each. The team consults several dog experts and kennel clubs to curate and update the information about dog breeds, not relying solely on gathered datasets.
The included source code provides a simple slide-show application, which processes the gesture recognition events from the runtime DLL to navigate through a series of images drawn from the ‘Pictures’ folders on your machine. Included in the sample is the ability to track and display multiple people, with the nearest person (shown in black) controlling the slide-show. Those not in control will be shown in gray. A person successfully completing a gesture will temporarily show as red:
The sample was developed by our team, and uses research from the Machine Learning and Perception group to provide a Random Decision Forest (RDF) based gesture recognizer trained using machine learning algorithms designed by Sebastian Nowozin.
A runtime DLL which captures real-time Kinect information, processes it through an advanced gesture recognition library, and triggers gesture events.
A C# source code sample showing how this runtime can be used to handle the events generated by actual gestures.
Microsoft® Touch Mouse
This is a mouse with a twist: a built-in multi-touch sensor and gesture recognition software. The Microsoft® Touch Mouse was produced in collaboration with Microsoft Hardware (including The Applied Sciences Lab) and Microsoft Research, incorporating innovations from the Mouse 2.0 research project. Working with Mouse 2.0 researchers and Microsoft Hardware, The MSR UXT team produced an instrumented research platform for evaluating Touch Mouse’s gesture support, and implemented the final contact tracking and gesture recognition engine. The end result is a mouse supporting a family of gestures for working with Microsoft Windows 7.
Photo collages celebrate important events and themes in our lives. Microsoft Research presents AutoCollage, an advanced computer vision and image processing program which automatically creates collages of your pictures. Face detection, saliency filters, and other Microsoft research identifies interesting parts of pictures. Advanced object selection and blending technologies seamlessly combine these pieces into a beautiful new AutoCollage. Pick a folder, press a button, and in a few minutes AutoCollage presents you with a unique memento to print or email to your family and friends.
Millions of people download files over the internet every day, and servers can’t always keep up with the demand. Secure peer accelerated downloads distribute authorized files to more people more quickly than any server can alone. Based on Network Coding research, Microsoft Research’s secure peer accelerated downloads use proven security technologies like TLS and digital certificates in innovative ways, protecting clients and publishers alike. We also use the latest networking technologies like Teredo and IPv6 to help computers communicate with each other in situations they otherwise could not. Secure Peer Accelerated Downloads with network coding – embodied in the Microsoft Secure Content Downloader – were used to distribute Visual Studio 2008 Beta-2 to customers.