Indoor frame recovering via line segments refinement and voting

Frame structure estimation from line segments is an important yet challenging problem in understanding indoor scenes. In practice, line segment extraction can be affected by occlusions, illumination variations, and weak object boundaries. To address this problem, an approach for frame structure recovery based on line segment refinement and voting is proposed. We refined line segments by the revising, connecting, and adding operations. We then propose an iterative voting mechanism for selecting refined line segments, where a cross ratio constraint is enforced to build crab-like models. Our algorithm outperforms state-of-the-art approaches, especially when considering complex indoor scenes.