Proceedings of the 18th annual conference on Computer graphics and interactive techniques
ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2006 Papers
Noise Estimation from a Single Image
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Technical Section: Real-time temporal shaping of high-speed video streams
Computers and Graphics
Fusion of fragmentary classifier decisions for affective state recognition
MPRSS'12 Proceedings of the First international conference on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction
Automated video looping with progressive dynamism
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Phase-based video motion processing
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Assistive living robot: a remotely controlled robot for older persons living alone
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
Whose "city of tomorrow" is it?: on urban computing, utopianism, and ethics
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
Joint view expansion and filtering for automultiscopic 3D displays
ACM Transactions on Graphics (TOG)
A data set of real world driving to assess driver workload
Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Noncontact automatic heart rate analysis in visible spectrum by specific face regions
Proceedings of the 14th International Conference on Computer Systems and Technologies
Evaluating the use of ECG signal in low frequencies as a biometry
Expert Systems with Applications: An International Journal
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Our goal is to reveal temporal variations in videos that are difficult or impossible to see with the naked eye and display them in an indicative manner. Our method, which we call Eulerian Video Magnification, takes a standard video sequence as input, and applies spatial decomposition, followed by temporal filtering to the frames. The resulting signal is then amplified to reveal hidden information. Using our method, we are able to visualize the flow of blood as it fills the face and also to amplify and reveal small motions. Our technique can run in real time to show phenomena occurring at the temporal frequencies selected by the user.