Three-Dimensional Reconstruction of Dynamic Scenes Based on Deep Learning
Abstract： The project aims at the structure and motion recovery of dynamic environments from un-calibrated image sequences. Three unsolved problems will be studied in this project. The first one is a framework of 3D reconstruction of dynamic scenes; the second is a reliable motion detection strategy based on deep belief networks; and the third is a robust 3D reconstruction algorithm. The main contributions are as follows. (i) The structure and motion of dynamic environments are recovered in trajectory space via matrix factorization; (ii) the deep belief networks are first introduced to classify the motion modes of the dynamic scenes; and (iii) a robust 3D reconstruction algorithm of dynamic scenes is proposed to handle outliers, large measurement errors, and missing data problems. The results of this project will fill a void in structure from motion of dynamic environments and provide a theoretical and practical guidance of other related problems.
Keywords: 3D reconstruction; motion estimation; deep learning; computer vision
Contact:
WANG Guanghui
E-mail: ghwangca@gmail.com