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Eulerian Video Magnification

Eulerian Video Magnification
banner slider Many seemingly static scenes contain subtle changes that are invisible to the naked human eye. However, it is possible to pull out these small changes from videos through the use of algorithms we have developed. We give a way to visualize these small changes by amplifying them and we present algorithms to pull out interesting signals from these videos, such as the human pulse, sound from vibrating objects and the motion of hot air. Videos Software and Code Eulerian Video Magnification code Matlab code and executables implementing Eulerian video processing for amplifying color and motion changes. Phase Based Video Motion Processing code Matlab code for implementing the new and improved phase-based motion magnification pipeline. Videoscope Web interface for motion and color magnification. Publications (Magnifying Motion and Color Changes) Publications (Analysis of Small Motions) People Faculty: Students, Postdocs and Affiliates: Collaborators: Edward H. Talks Related:  Computer Vision

Welcome - OpenCV Wiki Livehoods – Use-based urban analytics In conceptualizing and exploring the city we rely a range of smaller areas—neighbourhoods, boroughs, wards and districts—in order to make urban space intelligible. While we can readily discuss how neighbourhoods are shaped by physical geography (topography, adjacency to lakes or rivers, etc.), ordinance (zoning, access to public transit) and economics (real estate prices, average resident income), machine learning does not really spring to mind when we are considering how we might define ‘a neighbourhood’. Livehoods is a new project hatched within the School of Computer Science at Carnegie Mellon University that leverages 18 million Foursquare check-ins to draft up new urban ‘activity zones’ based on the patterns of frequent visitors. | School of Computer Science at Carnegie Mellon University

fMRI Evidence of ‘Mirror’ Responses to Geometric Shapes Mirror neurons may be a genetic adaptation for social interaction [1]. Alternatively, the associative hypothesis [2], [3] proposes that the development of mirror neurons is driven by sensorimotor learning, and that, given suitable experience, mirror neurons will respond to any stimulus. This hypothesis was tested using fMRI adaptation to index populations of cells with mirror properties. After sensorimotor training, where geometric shapes were paired with hand actions, BOLD response was measured while human participants experienced runs of events in which shape observation alternated with action execution or observation. Adaptation from shapes to action execution, and critically, observation, occurred in ventral premotor cortex (PMv) and inferior parietal lobule (IPL). Figures Citation: Press C, Catmur C, Cook R, Widmann H, Heyes C, et al. (2012) fMRI Evidence of ‘Mirror’ Responses to Geometric Shapes. Editor: Alessio Avenanti, University of Bologna, Italy Copyright: © 2012 Press et al.

Statistical Formulas For Programmers By Evan Miller DRAFT: May 19, 2013 Being able to apply statistics is like having a secret superpower. Where most people see averages, you see confidence intervals. When someone says “7 is greater than 5,” you declare that they're really the same. In a cacophony of noise, you hear a cry for help. Unfortunately, not enough programmers have this superpower. As my modest contribution to developer-kind, I've collected together the statistical formulas that I find to be most useful; this page presents them all in one place, a sort of statistical cheat-sheet for the practicing programmer. Most of these formulas can be found in Wikipedia, but others are buried in journal articles or in professors' web pages. Send suggestions and corrections to Table of Contents 1. One of the first programming lessons in any language is to compute an average. 1.1 Corrected Standard Deviation The standard deviation is a single number that reflects how spread out the data actually is. Where: SE=s√N 2. 3.

Human Interface Technology Lab - How the VRD works Using the VRD technology it is possible to build a display with the following characteristics: In a conventional display a real image is produced. The real image is either viewed directly or projected through an optical system and the resulting virtual image is viewed. With the VRD no real image is ever produced. Instead, an image is formed directly on the retina of the user's eye. The resulting modulated beam is then scanned to place each image point, or pixel, at the proper position on the retina. In the original prototype the faster horizontal scanning is accomplished with an acousto-optical modulator and the vertical scanning with a galvanometer to produce a 1280 pixel by 1024 line raster that is updated at 72 Hertz. To overcome the limitations of the acousto-optical modulator HITL engineers have developed a proprietary mechanical resonant scanner. After scanning, the optical beam must be properly projected into the eye.

Data visualisation DIY: our top tools | News What data visualisation tools are out there on the web that are easy to use - and free? Here on the Datablog and Datastore we try to do as much as possible using the internet's powerful free options. That may sound a little disingenuous, in that we obviously have access to the Guardian's amazing Graphics and interactive teams for those pieces where we have a little more time - such as this map of public spending (created using Adobe Illustrator) or this Twitter riots interactive. But for our day-to-day work, we often use tools that anyone can - and create graphics that anyone else can too. So, what do we use? Google fusion tables This online database and mapping tool has become our default for producing quick and detailed maps, especially those where you need to zoom in. The main advantage is the flexibility - you can can upload a kml file of regional borders, say - and then merge that with a data table. This excellent tutorial by Google's Kathryn Hurley is a great place to start. Datamarket

Gettier and justified true belief: fifty years on | The Philosophers Magazine On the fiftieth anniversary of Gettier’s famous paper, Fred Dretske explains what we should have learned from it. This article appears in Issue 61 of The Philosophers’ Magazine. Please support TPM by subscribing. This is the golden – the fiftieth – anniversary of Edmund Gettier’s remarkable paper on why knowledge isn’t justified true belief. It seems like an appropriate time, therefore, to evaluate what we have learned – or should have learned – from his elegant counterexamples. Gettier’s paper had a tremendous impact on contemporary epistemology. Gettier’s counterexamples are constructed on the basis of two assumptions about justification, both of which were (at the time he made them) entirely uncontentious. 1: The justification one needs to know that P is true is a justification one can have for a false proposition. Almost all philosophers who aren’t sceptics accept 1 without hesitation. But, alas, accepting both 1 and 2 lands you in deep trouble. The problem is not solved.

Big-O Algorithm Complexity Cheat Sheet Blinded by the Light: DIY Retinal Projection After grabbing a couple of Microvision SHOWWX laser picoprojectors when they went up on Woot a few months back, I started looking for ways to use them. Microvision started out of a project at the University of Washington HITLab in 1994 to develop laser based virtual retinal displays. That is, a display that projects an image directly onto the user’s retina. This allows for a potentially very compact see through display that is only visible by the user. The setup I built is basically what Michael Tidwell describes in his Virtual Retinal Displays thesis. Aside from my inability to find properly shaped mirrors, the big weakness of this rig is the size of the exit pupil. If you do want to build something like this, keep in mind that the title of this post is only half joking. blinded.scadblinded.stl Related Posts

Subversive Cartographies What are subversive cartographies? This issue is addressed a series of presentations organized by Chris Perkins (University of Manchester) and Jörn Seemann (Louisiana State University) for the upcoming 2008 Association of American Geographers meeting (Boston, April 15-19 2008). “To be subversive, is to wish to overthrow, destroy or undermine the principles of established orders. As such subversive cartographies offer alternative representations to established social and political norms. Subversive Cartographies 1: Papers emphasizing the role of the aesthetic in the construction of alternative and artistic mappings. Deconstructing Intentionally Manipulative Maps (IMMs) Ian Muehlenhaus, University of Minnesota Radical Cartography: Artists Making Activist Maps Lize Mogel, Interdisciplinary Artist Decolonizing Historical Cartography Through Narrative: Champlain’s Voyages Revisited Margaret Wickens Pearce, Ohio University and Michael Hermann, University of Maine Discussant: Vincent J.

"The mind is willing, but the flesh is weak": th... [Psychol Sci. 2012] Essential Math for Games Programmers As the quality of games has improved, more attention has been given to all aspects of a game to increase the feeling of reality during gameplay and distinguish it from its competitors. Mathematics provides much of the groundwork for this improvement in realism. And a large part of this improvement is due to the addition of physical simulation. Creating such a simulation may appear to be a daunting task, but given the right background it is not too difficult, and can add a great deal of realism to animation systems, and interactions between avatars and the world. This tutorial deepens the approach of the previous years' Essential Math for Games Programmers, by spending one day on general math topics, and one day focusing in on the topic of physical simulation. Topics for the various incarnations of this tutorial can be found below. Current Materials Slides The latest available versions of the slides for the math tutorials at GDC 2015 are as follows: Past Materials Core Mathematics

Researchers amplify variations in video, making the invisible visible At this summer's Siggraph — the premier computer-graphics conference — researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) will present new software that amplifies variations in successive frames of video that are imperceptible to the naked eye. So, for instance, the software makes it possible to actually "see" someone's pulse, as the skin reddens and pales with the flow of blood, and it can exaggerate tiny motions, making visible the vibrations of individual guitar strings or the breathing of a swaddled infant in a neonatal intensive care unit. The system is somewhat akin to the equalizer in a stereo sound system, which boosts some frequencies and cuts others, except that the pertinent frequency is the frequency of color changes in a sequence of video frames, not the frequency of an audio signal. The prototype of the software allows the user to specify the frequency range of interest and the degree of amplification. Happy accident

Nightingale’s Rose January 9, 2008, 4:06 pm By Henry Woodbury Two ways of reading the word area — its general vs. its mathematical meaning — leads to confusion in this otherwise superb article on Charts in the Economist. The chart in question is Florence Nightingale’s “Diagram of the Causes of Mortality in the Army of the East.” The data is plotted by month in 30-degree wedges. The Economist explains how to interpret the diagram: As with today’s pie charts, the area of each wedge is proportional to the figure it stands for, but it is the radius of each slice (the distance from the common centre to the outer edge) rather than the angle that is altered to achieve this. Herein lies the confusion. Our Creative Director, Piotr Kaczmarek, recalibrated Nightingale’s chart to correct this error. Nightingale’s diagram, often referred to as Nightingale’s Rose or Nightingale’s Coxcomb, represents one of the inherent risks in visual explanation. This is better: a stacked bar chart that introduces a scale (!) Comments