Image and Video Editing at MSR Cambridge

Established: January 23, 2002

At Microsoft Research in Cambridge we are developing new machine vision algorithms for intelligent image and video editing and browsing. Our technology provides tools for: accurate interactive segmentation and matting, color correction, easy object removal and image restoration, and seamless object insertion.

News!

AutoCollage is now available as a product from Microsoft Research Cambridge. Click here to get a free trial version.

Automatic Collage of a Photo Collection

AutoCollage is an automatic procedure for constructing a visually appealing collage from a collection of input images. The aim is that the resulting collage should be representative of the collection, summarising its main themes. It is also assembled largely seamlessly, using graph-cut, Poisson blending of alpha-masks, to hide the joins between input images. This work makes several new contributions. Firstly, we show how energy terms can be included that: encourage the selection of a representative set of images; that are sensitive to particular object classes; that encourage a spatially efficient and seamless layout. Secondly the resulting optimization poses a search problem that, on the face of it, is computationally infeasible. Rather than attempt an expensive, integrated optimization procedure, we have developed a sequence of optimization steps, from static ranking of images, through region of interest optimization, optimal packing by constraint satisfaction, and lastly graph-cut alpha-expansion. To illustrate the power of AutoCollage, we have used it to create collages of many home photo sets; we also conducted a user study in which AutoCollage outperformed competitive methods.

Please download: Video, User Study, Siggraph talk (ppt)

Additional Projects

(Interactive) Image Matting

go to project page

(Interactive) ImageSegmentation

go to project page

Out of Bounds Photography

go to project page

Unwrap Mosaic

go to project page

Automatic Photo Collage (AutoCollage)

Bayesian Color Constancy

go to external project page

Patchworks — for object removal

Blender — for object insertion

3D Video

ru

go to project page

 Computer Vision at MSR Cambridge

People

Publications

Digital Tapestry

Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov, Andrew Blake

January 2005