Feasible Self-Calibration of Larger Field-of-View (FOV) Camera Sensors for the Advanced Driver-Assistance System (ADAS)

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 15; p. 3369
• Main Authors: Kakani, Vijay, Kim, Hakil, Kumbham, Mahendar, Park, Donghun, Jin, Cheng-Bin, Nguyen, Van Huan
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 31.07.2019; MDPI
• Subjects: advanced driver-assistance system (ADAS); Algorithms; Calibration; International conferences; larger field-of-view (FOV); model-specific empirical γ-residual rectification factor; Optimization techniques; parameter sharing; Pattern recognition; radial distortions; Robotics; self-calibration; Sensors; United States > US; radial distortions; parameter sharing; larger field-of-view (FOV); model-specific empirical γ-residual rectification factor; advanced driver-assistance system (ADAS); self-calibration

This paper proposes a self-calibration method that can be applied for multiple larger field-of-view (FOV) camera models on an advanced driver-assistance system (ADAS). Firstly, the proposed method performs a series of pre-processing steps such as edge detection, length thresholding, and edge groupin...