PPT-Motion from Blur

Shengyang Dai and Ying Wu EECS Department Northwestern University NORTHWESTERN UNIVERSITY http visionmiddleburyeduflow Baker Scharstein Lewis Roth Black Szeliski ICCV07. OBox 100 FI33721 Tampere Finland Email ticoieeeorg ABSTRACT In this paper we investigate the problem of recovering the motion blur point spread function PSF by fusing the information available in two di64256erently exposed im age frames of the same s A static rendering of the scene is inset in the low er right and closeups are shown in be Strati64257ed sampling in b is very noisy at this low sample count Multidimensional Adaptive Sampling Hachisuka et al 2008 in c performs much better but still But after running hundreds of projects through the selection process on the GSX we have found there are some best practice essentials This isnt about prescribing a formula its about identifying the key structures of a successful pitch and sketching Lelgard a M Brdif a B Vallet a D Boldo b Universit Paris Est IGN Laboratoire MATIS 73 a venue de Paris 94165 SaintMand France lamanlelegard mathieubredif brunovalletign fr EDF RD Dpartement STEP 6 quai Watier 78401 C hatou France didierboldoedf edusg Chaoqiang Liu Center for Wavelets Approx and Info Proc National University of Singapore Singapore 117542 tslliucqnusedusg Abstract Restoration of a degraded image from motion blurring is highly dependent on the estimation of the blurring kernel Fig.1.Motionestimationanddeblurringofharmonicrotationusingourapproach.Thispaperaddressestwofundamentalproblemswhenusingthe utteredshutter:1)howtoapplytheFStohandleabroaderclassofmotionsand2)howtoautom Shengyang Dai . and. Ying Wu. EECS Department, Northwestern University. NORTHWESTERN. UNIVERSITY. http. ://vision.middlebury.edu/flow. /. Baker, . Scharstein. , Lewis, Roth, Black, Szeliski, . ICCV’07. Steven Lu. Overview. Significance of real-time motion blur rendering (Useful for what?). Slow performance of traditional methods. Some of the modern, more . efficient . methods . have problems, too. A new method is presented . Dec. 18, 2009, . Pacifico. Yokohama, . Japan. Lei Yang . H. , Diego . Nehab. . M. , Pedro V. Sander . H. , . Pitchaya. . Sitthi-amorn. . V. , Jason Lawrence . V. ,. Hugues. Hoppe . M. Outline. Ivan . Dimitrov. 508/2012. Filtering in . g. eneral . Widespread. Suitable for . Dataflow . Easily upgradable. 2/11. Applying the filter. To apply the filter on the current pixel, you need to use his neighbor pixels. Ivan . Dimitrov. 508/2012. . Photography. Fast . moving object or a longer exposure time may result in blurring . artifacts . The same effect can be achieved in a artificial way via image . procesing. Kinematics Terminology. Scalar vs. Vector. Scalar: . quantities that have only a size, but no direction. i. e. : . distance, speed. Vector: . quantities that have a size and direction. ie. : . displacement, velocity. Dec. 18, 2009, . Pacifico. Yokohama, . Japan. Lei Yang . H. , Diego . Nehab. . M. , Pedro V. Sander . H. , . Pitchaya. . Sitthi-amorn. . V. , Jason Lawrence . V. ,. Hugues. Hoppe . M. Outline. The next found image lives between what is real and a certain future surrealism. I wonder when I click, Do I manipulate the shot later or leave it as is, crop it or turn it into a photo painting, adding new elements, textures, ideas? On the street, the decisive moment emerges only as a focused blur..