Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is ll known that docking of Autonomous Underwater Vehicle (AUV) provides scope to perform long duration deep-sea exploration. A large amount of literature is available on vision-based docking which exploit mechanical design, colored markers to estimate the pose of a docking station. In this work,  propose a method to estimate the relative pose of a circular-shaped docking station (arranged with LED lights on periphery) up to five degrees of freedom (5-DOF, neglecting roll effect). Generally, extraction of light markers from underwater images is based on fixed/adaptive choice of threshold, follod by mass moment-based computation of individual markers as ll as center of the dock. Novelty of our work is the proposed highly effective scene invariant histogram-based adaptive thresholding scheme (HATS) which reliably extracts positions of light sources seen in active marker images. As the perspective projection of a circle features a family of ellipses,  then fit an appropriate ellipse for the markers and subsequently use the ellipse parameters to estimate the pose of a circular docking station with the help of a ll-known method in Safaee-Rad et al. (IEEE Trans Robot Autom 8(5):624---640, 1992).  analyze the effectiveness of HATS as ll as proposed approach through simulations and experimentation.  also compare performance of targeted curvature-based pose estimation with a non-iterative efficient perspective-n-point (EPnP) method. The paper ends with a few interesting remarks on vantages with ellipse fitting for markers and utility of proposed method in case of non-detection of all the light markers.
['Shatadal Ghosh', 'Ranjit Ray', 'Siva Ram Krishna Vadali', 'Sankar Nath Shome', 'S. Nandy']
I am writing a research paper on a idea Reliable pose estimation of underwater dock using single camera: a scene invariant approach
[{"from": "human", "value": "I am writing a research paper on a idea Reliable pose estimation of underwater dock using single camera: a scene invariant approach"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is ll known that docking of Autonomous Underwater Vehicle (AUV) provides scope to perform long duration deep-sea exploration. A large amount of literature is available on vision-based docking which exploit mechanical design, colored markers to estimate the pose of a docking station. In this work,  propose a method to estimate the relative pose of a circular-shaped docking station (arranged with LED lights on periphery) up to five degrees of freedom (5-DOF, neglecting roll effect). Generally, extraction of light markers from underwater images is based on fixed/adaptive choice of threshold, follod by mass moment-based computation of individual markers as ll as center of the dock. Novelty of our work is the proposed highly effective scene invariant histogram-based adaptive thresholding scheme (HATS) which reliably extracts positions of light sources seen in active marker images. As the perspective projection of a circle features a family of ellipses,  then fit an appropriate ellipse for the markers and subsequently use the ellipse parameters to estimate the pose of a circular docking station with the help of a ll-known method in Safaee-Rad et al. (IEEE Trans Robot Autom 8(5):624---640, 1992).  analyze the effectiveness of HATS as ll as proposed approach through simulations and experimentation.  also compare performance of targeted curvature-based pose estimation with a non-iterative efficient perspective-n-point (EPnP) method. The paper ends with a few interesting remarks on vantages with ellipse fitting for markers and utility of proposed method in case of non-detection of all the light markers."}]