9 June 2014 Robust real-time horizon detection in full-motion video
Author Affiliations +
Abstract
The ability to detect the horizon on a real-time basis in full-motion video is an important capability to aid and facilitate real-time processing of full-motion videos for the purposes such as object detection, recognition and other video/image segmentation applications. In this paper, we propose a method for real-time horizon detection that is designed to be used as a front-end processing unit for a real-time marine object detection system that carries out object detection and tracking on full-motion videos captured by ship/harbor-mounted cameras, Unmanned Aerial Vehicles (UAVs) or any other method of surveillance for Maritime Domain Awareness (MDA). Unlike existing horizon detection work, we cannot assume a priori the angle or nature (for e.g. straight line) of the horizon, due to the nature of the application domain and the data. Therefore, the proposed real-time algorithm is designed to identify the horizon at any angle and irrespective of objects appearing close to and/or occluding the horizon line (for e.g. trees, vehicles at a distance) by accounting for its non-linear nature. We use a simple two-stage hierarchical methodology, leveraging color-based features, to quickly isolate the region of the image containing the horizon and then perform a more ne-grained horizon detection operation. In this paper, we present our real-time horizon detection results using our algorithm on real-world full-motion video data from a variety of surveillance sensors like UAVs and ship mounted cameras con rming the real-time applicability of this method and its ability to detect horizon with no a priori assumptions.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Grace B. Young, Bryan Bagnall, Corey Lane, and Shibin Parameswaran "Robust real-time horizon detection in full-motion video", Proc. SPIE 9076, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XI, 90760N (9 June 2014); doi: 10.1117/12.2050455; https://doi.org/10.1117/12.2050455
PROCEEDINGS
7 PAGES


SHARE
Advertisement
Advertisement
Back to Top