Stage-based 3D scene reconstruction from single image

Holistic scene understanding is a major goal in recent research of computer vision. To deal with this task, reasoning the 3D relationship of components in a scene is identified as one of the key problems. We study this problem in terms of structural reconstruction of 3D scene from single view image. Our first step concentrates on geometrical layout analysis of scene using low-level features. We allocate images into seven recurring and stable geometry classes. This classification labels the image with rough knowledge of its scene geometry. Then, based on this geometry label, we propose an adaptive autonomous scene reconstruction algorithm which adopts specific approaches particularly for different scene types. We show, experimentally, given the right geometry label, low-quality uncalibrated monocular images from the benchmark dataset can be structurally reconstructed in 3D space in a time/effort efficient way. This robust approach does not require high quality or high complexity input image. We demonstrate the effectiveness of this approach in this paper.