GradientShop: A gradient-domain optimization framework for image and video filtering
ACM Transactions on Graphics (TOG)
Video stylization for digital ambient displays of home movies
NPAR '10 Proceedings of the 8th International Symposium on Non-Photorealistic Animation and Rendering
Do predictions of visual perception aid design?
ACM Transactions on Applied Perception (TAP)
Real-time spatiotemporal stereo matching using the dual-cross-bilateral grid
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Extended papers from NPAR 2010: Stylized ambient displays of digital media collections
Computers and Graphics
Saliency-based fidelity adaptation preprocessing for video coding
Journal of Computer Science and Technology - Special issue on natural language processing
Probabilistic models for robot-based object segmentation
Robotics and Autonomous Systems
Generation of coherent mosaic animations: enhancement and evaluation of temporal coherence
Computer Animation and Virtual Worlds
Streaming hierarchical video segmentation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Example-based video color grading
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Video segmentation with superpixels
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
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Video streams are ubiquitous in applications such as surveillance, games, and live broadcast. Processing and analyzing these data is challenging because algorithms have to be efficient in order to process the data on the fly. From a theoretical standpoint, video streams have their own specificities --- they mix spatial and temporal dimensions, and compared to standard video sequences, half of the information is missing, i.e. the future is unknown. The theoretical part of our work is motivated by the ubiquitous use of the Gaussian kernel in tools such as bilateral filtering and mean-shift segmentation. We formally derive its equivalent for video streams as well as a dedicated expression of isotropic diffusion. Building upon this theoretical ground, we adapt a number of classical algorithms to video streams: bilateral filtering, mean-shift segmentation, and anisotropic diffusion.