Dynamic 3D surface reconstruction and motion modeling from a pan–tilt–zoom camera

• We propose a method to recover the 3D motion and structure of a tracked target.
• We use a single pan–tilt–zoom camera tracking a freely moving target in real time.
• The structure and motion are updated sequentially while frames are captured.
• The 3D motion and structure are recovered using 50% of the frames captured.
• The method uses less execution time than the offline reconstruction approach.

3D surface reconstruction and motion modeling has been integrated in several industrial applications. Using a pan–tilt–zoom (PTZ) camera, we present an efficient method called dynamic 3D reconstruction (D3DR) for recovering the 3D motion and structure of a freely moving target. The proposed method estimates the PTZ measurements to keep the target in the center of the field of view (FoV) of the camera with the same size. Feature extraction and tracking approach are used in the imaging framework to estimate the target's translation, position, and distance. A selection strategy is used to select keyframes that show significant changes in target movement and directly update the recovered 3D information. The proposed D3DR method is designed to work in a real-time environment, not requiring all frames captured to be used to update the recovered 3D motion and structure of the target. Using fewer frames minimizes the time and space complexity required. Experimental results conducted on real-time video streams using different targets to prove the efficiency of the proposed method. The proposed D3DR has been compared to existing offline and online 3D reconstruction methods, showing that it uses less execution time than the offline method and uses an average of 49.6% of the total number of frames captured.