Abstract
Recent work has shown the improved depth reconstruction by combining depth and surface normal information. In this paper, we build on the findings and introduce novel variational methods for a refined depth reconstruction for a multi-line scanner using light field and photometric stereo data. In this specific setup, the object is acquired while moving on a conveyor belt in a defined direction under the camera, which simultaneously captures light field and photometric stereo data as the object is transported. We perform our experiments on virtual and real-world data and achieve significantly improved results over state-of-the-art methods both in depth and surface normal accuracy.