Research Blog: Motion Stills – Create beautiful GIFs from Live Photos
Kudos to the team from Machine Perception at Google Research that just launched the Motion Still App to generate novel photos on an iOS device. This work is in part aimed at combining efforts like Video Textures and Video Stabilization and a lot more. Source: Research Blog: Motion Stills – Create beautiful GIFs from Live […]
Paper in WACV (2015): “Egocentric Field-of-View Localization Using First-Person Point-of-View Devices”
Paper Abstract We present a technique that uses images, videos and sensor data taken from first-person point-of-view devices to perform egocentric field-of-view (FOV) localization. We define egocentric FOV localization as capturing the visual information from a person’s field-of-view in a given environment and transferring this information onto a reference corpus of images and videos of […]
Google I/O 2013: Secrets of Video Stabilization on YouTube
Presentation at Google I/0 2013 by Matthias Grundmann, John Gregg, and Vivek Kwatra on our Video Stabilizer on YouTube Video stabilization is a key component of YouTubes video enhancement tools and youtube.com/editor. All YouTube uploads are automatically detected for shakiness and suggested stabilization if needed. This talk will describe the technical details behind our fully […]
Paper in ECCV Workshop 2012: “Weakly Supervised Learning of Object Segmentations from Web-Scale Videos”
Paper / Citation Abstract We propose to learn pixel-level segmentations of objects from weakly labeled (tagged) internet videos. Espe cially, given a large collection of raw YouTube content, along with potentially noisy tags, our goal is to automatically generate spatiotemporal masks for each object, such as a “dog”, without employing any pre-trained object detectors. We formulate […]
Video Stabilization on YouTube
Here is an excerpt from a Google Research Blog on our Video Stabilization on YouTube. Now even more improved. One thing we have been working on within Research at Google is developing methods for making casual videos look more professional, thereby providing users with a better viewing experience. Professional videos have several characteristics that differentiate […]
Best Computer Vision Paper Award by Google Research for 2011
Our following paper was just awarded the Excellent Paper for 2011 in Computer Vision by Google Research. Casually shot videos captured by handheld or mobile cameras suffer from significant amount of shake. Existing in-camera stabilization methods dampen high-frequency jitter but do not suppress low-frequency movements and bounces, such as those observed in videos captured by […]
In the News (2011): "Shake it like an Instagram picture — Online Video News"
Our work, as described in the following paper, now showcased in youtube. [bibtex file=IrfanEssaWS.bib key=2011-Grundmann-AVSWROCP] YouTube effects: Shake it like an Instagram picture via YouTube effects: Shake it like an Instagram picture — Online Video News. YouTube users can now apply a number of Instagram-like effects to their videos, giving them a cartoonish or Lomo-like look with […]
PhD Fellowships from Google Research for Matthias Grundmann
Congratulations to Matthias Grundmann, winner of the Google PhD Fellowship in Computer Vision for 2012. via PhD Fellowships – Google Research. Google PhD Fellowship Program Overview Nurturing and maintaining strong relations with the academic community is a top priority at Google. The Google U.S./Canada PhD Student Fellowship Program was created to recognize outstanding graduate students […]