JOURNAL ARTICLE

Feature-Based Vision For Stochastic Motion Tracking Under Partial Occlusion

Abhishek ShastryAnubhav DattaInderjit Chopra

Year: 2022 Journal:   Proceedings of the Vertical Flight Society 78th Annual Forum Pages: 1-20

Abstract

This work is a continuation of the ship-deck landing research presented at VFS Forum 2021, which established a vision-based method to track ship-deck motion before landing when conditions are favorable. This paper makes advancements on two fronts: 1) Demonstrating the effect of velocity feedback on tracking stochastic deck motion, and 2) Developing a new feature-based vision system to detect and track decks in a wide range of challenging environments. The new vision system can detect decks in occlusion as high as 95%. It can also handle a wide range of illumination conditions varying from 20,000 lux of a bright day to 0.01 lux of a dark room. Moreover unlike fiducial-based vision systems that require a custom well designed marker or tag to work, the new vision system can work with generic ship-decks or landing platforms.

Keywords:
Computer vision Computer science Artificial intelligence Feature (linguistics) Track (disk drive) Deck Tracking (education) Tracking system Motion (physics) Range (aeronautics) Machine vision Engineering Kalman filter Aerospace engineering

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Topics

Maritime Navigation and Safety
Physical Sciences →  Engineering →  Ocean Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Ship Hydrodynamics and Maneuverability
Physical Sciences →  Engineering →  Ocean Engineering

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