In-loop feature tracking for structure and motion with out-of-core optimization

Abstract

In this paper, a novel and approach for obtaining 3D models from video sequences captured with hand-held cameras is addressed. We define a pipeline that robustly deals with different types of sequences and acquiring devices. Our system follows a divide and conquer approach: after a frame decimation that pre-conditions the input sequence, the video is split into short-length clips. This allows to parallelize the reconstruction step which translates to a reduction in the amount of computational resources required. The short length of the clips allows an intensive search for the best solution at each step of reconstruction which robustifies the system. The process of feature tracking is embedded within the reconstruction loop for each clip as a difference with other approaches. A final registration step, merges all the processed clips to the same coordinate frame.

Augmented reality over video stream acquired from UAVs for operations support

“…Sparse reconstruction of the viewed terrain in Experiment 1 (Sect. 3.3), including the trajectory (camera poses) of the UAV during the ight.we use SfM algorithms such as[129] or[130] that can exploit the calibrated camera constraint. First, two images with sucient parallax are selected to initialize the reconstruction.…”