Budges355: Individual events of a bird's flying motion, along with video clips, annotated images and 3D data (355 clips).

Published: 14 March 2022| Version 1 | DOI: 10.17632/p5w3t7vw4f.1
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Description

The dataset consists of birds (Budgerigar) flying motion in a controlled environment. Trajectories of birds flying from one perch to another perch were recorded using video cameras. The dataset contains 355 clips of individual events of a bird's flying motion, along with annotated images and 3D data generated from the events. Only the bird in motion was annotated and 3D trajectories were calculated for all five parts of the bird that were annotated. The annotations were done manually using Computer Vision Annotation Tool (CVAT). For generating the 3D trajectories of the bird's flight motion, Matlab (MathWorks®) was used. The files for all five 3D trajectories are labelled as such; point3D_bird for the bird’s body, point3D_head for the head of the bird, point3D_tail for the tail of the bird, point_3D_left_wing and point_3D_right_wing for the left wing and right wing of the bird respectively. The annotation's file format is JSON, and the format of the annotation is Microsoft COCO . The 3D coordinates for the bird's trajectories are in .mat file format. Dataset folder structure:  clip_1  -->point3D_bird  -->point3D_head  -->point3D_tail  -->point3D_left_wing  -->point3D_right_wing  -->left.mp4  -->right.mp4  -->left  -->-->images (includes all the frames of clip 1 left)  -->-->annotations (includes .json file for annotation of clip 1 left)  -->right  -->-->images (includes all the frames of clip 1 right)  -->-->annotations (includes .json file for annotation of clip 1 right) . . .  clip_355 There are two zip files: 1. Budges355 (Random 10 clips) where you can randomly find 10 clips for previewing the dataset. 2. Budges355 (clip 1-355).zip where you can find full dataset

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Steps to reproduce

This dataset was created with the sole motive that it will spur new and exciting computer vision research in the bio-inspired areas.

Categories

Computer Vision, Bio-Inspired System, 3D Analysis

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