Although I don't have first hand experience with the code, a former labmate of mine (I'm at the Univ. of Washington, and he's now at Google) is one of the leading experts on this area of research, and his VisualSFM [1] tool is, I think, the best and easiest-to-use available online.

Briefly, there are three main steps required to go from images to a 3d viewer like PhotoSynth:

1. Figure out where each image was shot from (the "camera pose") and get a sparse set of 3d points from the scene. These two are estimated simultaneously using bundle adjustment [2].

2. Go from a sparse set of 3d points to a dense 3d model. This is done using a technique called Multiple View Stereo (MVS), of which the leading (open) implementations are PMVS/CMVS [3,4].

3. Build an image-based rendering system that intelligently blends between the 3d models and images to minimize artifacts.

The VisualSFM software will do steps 1 and 2. Step 3 is still quite a challenging problem, but depending on what you're doing, you could use standard 3d modeling environments to look at your data.

[1] http://ccwu.me/vsfm/

[2] http://en.wikipedia.org/wiki/Bundle_adjustment

[3] http://www.di.ens.fr/pmvs/

[4] http://www.di.ens.fr/cmvs/