Work

Kalman-YOLO Improving YOLO Tracking Performance through the Integration of a Kalman Filter for a Beach Cleaning Robot

Year: 2025

Type: conference-paper

Abstract: Ocean waste poses a significant threat to both human and marine life as industries and individuals continue to dump garbage into the ocean.Sea creatures are poisoned by materials such as plastics and chemicals, which in turn contaminate humans who consume them.This paper introduces an innovative approach using Image Instance Segmentation with YOLOv8 to segment and track beach garbage.However, YOLOv8's object tracking struggles in dynamic environments with challenges like occlusion, shadows, and perspective changes in RGB frames.To address this, the author presents Kalman-YOLO, combining the Kalman Filter with YOLO for improved performance.Results show notable performance improvement, especially in tracking garbage for the Beach Cleaning Robot.

Source: Proceedings of International Conference on Artificial Life and Robotics

DOI: 10.5954/icarob.2025.os11-3

Authors: Rut Yatigul, Chi Jie Tan, Gamolped Prem, Eiji Hayashi

Institution: Kyushu Institute of Technology

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDGs: Responsible consumption and production, Life below water

Open Access status: bronze

OpenAlex ID: W4409906992