title: Design and Analysis of a Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs).
abstract: We describe the design and 3D sensing performance of an omnidirectional stereo (omnistereo) vision system applied to Micro Aerial Vehicles (MAVs). The proposed omnistereo sensor employs a monocular camera that is co-axially aligned with a pair of hyperboloidal mirrors (a vertically-folded catadioptric configuration). We show that this arrangement provides a compact solution for omnidirectional 3D perception while mounted on top of propeller-based MAVs (not capable of large payloads). The theoretical single viewpoint (SVP) constraint helps us derive analytical solutions for the sensor's projective geometry and generate SVP-compliant panoramic images to compute 3D information from stereo correspondences (in a truly synchronous fashion). We perform an extensive analysis on various system characteristics such as its size, catadioptric spatial resolution, field-of-view. In addition, we pose a probabilistic model for the uncertainty estimation of 3D information from triangulation of back-projected rays. We validate the projection error of the design using both synthetic and real-life images against ground-truth data. Qualitatively, we show 3D point clouds (dense and sparse) resulting out of a single image captured from a real-life experiment. We expect the reproducibility of our sensor as its model parameters can be optimized to satisfy other catadioptric-based omnistereo vision under different circumstances.
authors: Deptartment of Computer Science, The Graduate Center, The City University of New York (CUNY), 365 Fifth Avenue, New York, NY 10016, USA. cjaramillo@gradcenter.cuny.edu.
authors: Carlos
authors: C
authors: Jaramillo
authors: Electrical Engineering Department, The City College, City University of New York (CUNY City College), Convent Ave & 140th Street, New York, NY 10031, USA. rvalenti@ccny.cuny.edu.
authors: Roberto G
authors: RG
authors: Valenti
authors: Automation Department, Nanjing University of Science and Technology (NUST), Nanjing 210094, China. laura0955@live.cn.
authors: Ling
authors: L
authors: Guo
authors: Electrical Engineering Department, The City College, City University of New York (CUNY City College), Convent Ave & 140th Street, New York, NY 10031, USA. jxiao@ccny.cuny.edu.
authors: Jizhong
authors: J
authors: Xiao
mesh_terms: D000401:Aircraft; D004867:Equipment Design; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000295:instrumentation*; D010780:Photogrammetry / Q000295:instrumentation; D010781:Photography / Q000379:methods*
keywords: 3D perception; Micro Aerial Vehicles (MAVs); catadioptrics; omnistereo