Bird Observation Dataset, Yogyakarta 2025

The Bird Observation Dataset is a collection of original bird images acquired from a private data collection campaign conducted in Yogyakarta City, Indonesia, during November 2025. The dataset was developed to support research in bird detection, visual recognition, and object differentiation in outdoor environments, particularly for applications related to aerial surveillance and computer vision. All images were captured directly by the authors using DSLR cameras, ensuring high-quality visual data under natural imaging conditions. Image acquisition was carried out during three different time periods—daytime, late afternoon, and nighttime—to capture variations in illumination, background appearance, and visibility. This multitemporal acquisition strategy enables realistic representation of outdoor lighting transitions, including strong daylight, sunset conditions, and low-light nighttime scenes. The dataset includes diverse bird appearances with variations in orientation, scale, flight posture, and distance from the camera, as well as complex backgrounds such as urban structures, vegetation, and open sky typical of the Yogyakarta area. As the images were collected in real-world environments without artificial scene manipulation, the dataset reflects natural environmental complexity, including motion blur and background clutter. This dataset can be used independently or in combination with drone datasets to support research on false-positive reduction in drone detection systems, bird classification, and aerial object discrimination. The dataset is intended for academic and non-commercial research purposes.

The dataset is organized into image folders according to acquisition time periods and annotation availability:

1. Birds_01>>Images_Daytime/ — Bird images captured under daylight conditions
2. Birds_02>>Images_Afternoon/ — Bird images captured during late afternoon or sunset
3. Birds_03>>Images_Night/ — Bird images captured under nighttime illumination
4. Annotations/ — Annotation files (if applicable), provided in standard computer vision formats
5. Documentation/ — Dataset description and usage notes

All image files are provided in standard image formats (e.g., JPG or PNG) suitable for direct use in computer vision pipelines.