Line-circle: a geometric filter for single camera edge-based object detection

Tafrishi, Seyed Amir ORCID: https://orcid.org/0000-0001-9829-3144 and Kandjani, Vahid E. 2018. Line-circle: a geometric filter for single camera edge-based object detection. Presented at: 2017 5th RSI International Conference on Robotics and Mechatronics (ICRoM), Tehran, Iran, 25-27 October 2017. 2017 5th RSI International Conference on Robotics and Mechatronics (ICRoM). IEEE, 10.1109/ICRoM.2017.8466193

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Abstract

This paper presents a state-of-the-art approach in object detection for being applied in future simultaneous localization and mapping (SLAM) problems. Although, many SLAM methods are proposed to create suitable autonomy for mobile robots namely ground vehicles, they still face overconfidence and large computations during entrance to immense spaces with many landmarks. In particular, they suffer from impractical applications via sole reliance on the limited sensors like camera. Proposed method claims that unmanned ground vehicles without having huge amount of database for object definition and highly advance prediction parameters can deal with incoming objects during straight motion of camera in realtime. Line-Circle (LC) filter tries to apply detection, tracking and learning to each defined experts to obtain more information for judging scene without over-calculation. In this filter, circle expert let us summarize edges in groups. The Interactive feedback learning between each expert creates minimal error that fights against overwhelming landmark signs in crowded scenes without mapping. Our experts basically are dependent on trust factors' covariance with geometric definitions to ignore, emerge and compare detected landmarks. The experiment for validating the model is taken place via a camera beside an inertial measurement unit sensor for location estimation.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering Computer Science & Informatics
Publisher:	IEEE
ISBN:	978-1-5386-5703-4
Date of First Compliant Deposit:	4 February 2023
Date of Acceptance:	23 May 2016
Last Modified:	10 Feb 2023 14:45
URI:	https://orca.cardiff.ac.uk/id/eprint/156499

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