UCLA

Understanding of a incoming video sequence is one of the key parts of modern computer vision. Visualization of all the details that a computer understands about a certain video sequence is a very important tool to evaluate a vision system. In this paper, we propose a method for visualizing a 2D video sequence in a 3D space, which is based on the data of DARPA project.

The visualization started with the reconstruction of 3D space depended on the 2D video sequence data information. The use of homographic transformation for a structured light system reduced the computational cost of the system, since it only needed one image of the underlying environment. The smoothing of 3D trajectories of moving person was calculated from detection results. All the human skeleton models were from a pre-created 3D skeleton library. Aligning all the skeletons was a challenging problem in this project. We used the human-object interaction relationship and temporal information of the trajectories, such as motion information, trying to put the skeletons in the correct place. The results showed that visualization was a good way to express the understanding results of a computer vision system.