I've been reading some of the recent CVPR 2010 papers (check out the CVPR papers on the web page to see the full list), and I came a cool video produced by Yasutaka Furukawa. I met Yasutaka when I was a visitor at Jean Ponce's WILLOW group in Paris during Spring 2008, and I was truly amazed by some of the cool geometry-based work he has done. Being a recognition/machine-learning guy myself, I can only appreciate and wonder at the amazing work produced by in-depth knowledge of geometry. In this particular case, the images aren't ones that Yasutaka collected himself. The idea behind internet-scale vision is that you can use the millions of photos on sites such as Flickr.
Here is a cool video below, very much in the spirit of Photosynth.
It is also not a surprise to find that Yasutaka is now working at Google. One can only imagine where Google is going to apply the "Street-View" mentality next. Cities like NYC already have nice high-resolution building facades, see picture below from Google Earth Blog.
I want to one day run all of my object recognition experiments on Google Street view, and there is probably only a handful of places in the world that have the computational infrastructure to play with such experiments. I drool at the idea of one day building a Visual Memex from billions of online images (and this can only happen at at place like Google).
Wednesday, April 14, 2010
Monday, April 05, 2010
This is the title of a powerful treatise written by Clay Shirky, in which he strives to "convince you that a lot of what we think we know about categorization is wrong." Much thanks to David Weinberger's blog www.everythingismiscellaneous.com for pointing out this article. The take home message is quite similar to some of the "Beyond Categories" ideas I've tried to promulgate in my meager attempt to understand why progress in computer vision has reached a standstill. For anybody interested in understanding the limitations of classical systems of categorization, this article is a worth a read.
Back in 2005, I remember meeting Kristen Grauman at MIT's accepted PhD student open house. Back then she was a PhD student under Trevor Darrell (and is known for her work on the Pyramid Match Kernel), but now she has her own vision group at UT-Austin. She is the the advisor behind many cool vision projects there, and here are a few segmenatation/categorization related papers from the upcoming CVPR2010 conference. I look forward to checking out these papers because they are relevant to my own research interests. NOTE: some of the papers links are still not up -- I just used the links from Kristen's webpage.
Object-Graphs for Context-Aware Category Discovery. Y. J. Lee and K. Grauman
Collect-Cut: Segmentation with Top-Down Cues Discovered in Multi-Object Images. Y. J. Lee and K. Grauman
Asymmetric Region-to-Image Matching for Comparing Images with Generic Object Categories. J. Kim and K. Grauman