Localization Task
Localization tasks, aiming to pinpoint the location of objects or agents within an image or environment, are a central focus in computer vision and robotics. Current research emphasizes improving accuracy and efficiency using various approaches, including Siamese networks for image retrieval, convolutional neural networks (CNNs) and transformers for feature extraction and localization map generation, and self-supervised learning techniques to reduce reliance on labeled data. These advancements are crucial for applications ranging from autonomous navigation and robotics to medical image analysis and augmented reality, driving progress in both theoretical understanding and practical deployment of robust localization systems.
Papers
Learning to Estimate the Pose of a Peer Robot in a Camera Image by Predicting the States of its LEDs
Nicholas Carlotti, Mirko Nava, Alessandro Giusti
An experimental evaluation of Siamese Neural Networks for robot localization using omnidirectional imaging in indoor environments
J. J. Cabrera, V. Román, A. Gil, O. Reinoso, L. Payá