Thursday, October 4, 2012

Photoconsistency Visual Odometry II

I have been working on new features and modifications for my Photoconsistency Visual Odometry project. In the last version I have implemented two more C++ classes to estimate the 3D rigid transformation between two RGBD frames. In these new classes, the residuals and jacobians are computed analytically, significantly improving performance. 

Top: resulting 3D map using the new Photoconsistency Visual Odometry implementation. Bottom: visualization of the estimated trajectory over the ground-truth using the CVPR tools.
The changes do not end up there; now the source code is organized in two different parts: the phovo library, which contains the Photoconsistency Visual Odometry algorithms; and applications that use this library. This way you can select to just build the phovo library (which only depends on OpenCV, Eigen and OpenMP), or configure the project to compile the provided applications too. Furthermore, I have implemented two new classes to access the Kinect sensor data for online operation.

If you want to give it a try, please download the latest code from and build your own 3D maps with your Kinect sensor.