Monocular Depth Cues in Computer Vision Applications

Abstract

In the computer vision field, if image depth information were available, many tasks could be posed from a different perspective for the sake of higher performance and robustness. In our thesis, we have demonstrated how coarse depth information can be integrated in different tasks following alternative strategies to obtain more precise and robust results in three computer vision applications:
camera rotation parameters estimation, background estimation and pedestrian candidate generation.