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Stanford's New Website Converts Your Photos to 3D
An anonymous reader writes to tell us that Stanford has a new website that not only shows you how cool their new 3-d modeling system is, but actually allows you to give it a try with your own photos. The system can take a 2-d still image and estimate a detailed 3-d structure which you can navigate. "For each small homogeneous patch in the image, we use a Markov Random Field (MRF) to infer a set of "plane parameters" that capture both the 3-d location and 3-d orientation of the patch. The MRF, trained via supervised learning, models both image depth cues as well as the relationships between different parts of the image. Other than assuming that the environment is made up of a number of small planes, our model makes no explicit assumptions about the structure of the scene; this enables the algorithm to capture much more detailed 3-d structure than does prior art (such as Saxena et al., 2005, Delage et al., 2005, and Hoiem et el., 2005), and also give a much richer experience in the 3-d flythroughs created using image-based rendering, even for scenes with significant non-vertical structure."
About 20 years ago when they colorized Casablanca an office mate of mine was complaining about their ruining a perfectly good movie. I told him that he would be complaining even more when they used technology to make it in 3D. Seems that won't be too far away any more.
Wow, can you imagine how cool this would be with respect to video games? Drop in some photos, crank up the customized first person shooter, and zoooom! You could even take photos or shots from movies and do the same thing (e.g., using Star Wars stills).
There can be NO END to the verys to describe how much of a very, very, VERY bad idea making a CounterStrike map of your school/mall/town/etc would be.
Radar and Lidar are good for some applications, but they're fundamentally quite different. They're both active sensing technologies- they send out energy in part of the electromagnetic spectrum and then look in that narrow range of the spectrum and see what bounces back. This means that you have trouble seeing things farther away since you'd have to throw more and more energy to keep your samples uniformly bright or uniformly spaced. And it means your power requirements are much higher.
I think the most interesting part of computer vision is that which deals with passive sensing, such as this work. It senses the electromagnetic radiation that comes from our sun, or moon, or man-made sources. By using the same spectrum that our eyes use it should be able to get a qualitative understanding of the world similar to what humans can achieve.
Also, as humans we've built the world to be visually interpreted at the EM frequencies that we sense. This means our signs are readable in those frequencies, our indoor lighting works in those frequencies, etc... By sensing in those frequencies you make sure you don't miss anything that humans can see.
Wow, can you imagine how cool this would be with respect to video games? Drop in some photos, crank up the customized first person shooter, and zoooom! You could even take photos or shots from movies and do the same thing (e.g., using Star Wars stills).
There can be NO END to the verys to describe how much of a very, very, VERY bad idea making a CounterStrike map of your school/mall/town/etc would be. The crazy old men from florida have won
You can't take the sky from me...