2007 · 257 citations · 34 references
ComputingFine ArtsComputer VisionPhotographyRenderingImage RetrievalScene Reconstruction3D Scene UnderstandingCompositingImage CompositingInsertion AutomationObject SegmentationObject Size EstimationObjectsScene Representation
We present a system for inserting new objects into existing photographs by querying a vast image-based object library, pre-computed using a publicly available Internet object database. The central goal is to shield the user from all of the arduous tasks typically involved in image compositing. The user is only asked to do two simple things: 1) pick a 3D location in the scene to place a new object; 2) select an object to insert using a hierarchical menu. We pose the problem of object insertion as a data-driven, 3D-based, context-sensitive object retrieval task. Instead of trying to manipulate the object to change its orientation, color distribution, etc. to fit the new image, we simply retrieve an object of a specified class that has all the required properties (camera pose, lighting, resolution, etc) from our large object library. We present new automatic algorithms for improving object segmentation and blending, estimating true 3D object size and orientation, and estimating scene lighting conditions. We also present an intuitive user interface that makes object insertion fast and simple even for the artistically challenged.
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LabelMe: A Database and Web-Based Tool for Image Annotation
Bryan Russell, Antonio Torralba, Kevin Murphy et al. · International Journal of Computer Vision · 2007 · 4.2K citations · Full text
Noah Snavely, Steven M. Seitz, Richard Szeliski · ACM Transactions on Graphics · 2006 · 2.8K citations · Full text