BirdsEye-RU: A Dataset For Detecting Faces from Overhead Images
Md. Ahanaf Arif Khan, Ariful Islam, Sangeeta Biswas, Md. Iqbal Aziz Khan, Subrata Pramanik, Sanjoy Kumar Chakravarty, Bimal Kumar Pramanik
TL;DR
BirdsEye-RU is a new dataset comprising nearly 3,000 overhead images with over 8,000 annotated faces, aimed at improving face detection in challenging aerial and drone imagery.
Contribution
The paper introduces the BirdsEye-RU dataset, specifically designed for detecting small and distant faces in overhead images, filling a gap in existing datasets.
Findings
Dataset contains 2,978 images with over 8,000 annotated faces.
Includes drone and high-altitude smartphone images.
Publicly available for research use.
Abstract
Detecting faces in overhead images remains a significant challenge due to extreme scale variations and environmental clutter. To address this, we created the BirdsEye-RU dataset, a comprehensive collection of 2,978 images containing over eight thousand annotated faces. This dataset is specifically designed to capture small and distant faces across diverse environments, containing both drone images and smartphone-captured images from high altitude. We present a detailed description of the BirdsEye-RU dataset in this paper. We made our dataset freely available to the public, and it can be accessed at https://www.kaggle.com/datasets/mdahanafarifkhan/birdseye-ru.
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Taxonomy
TopicsFace recognition and analysis · Advanced Neural Network Applications · Face and Expression Recognition