| | --- |
| | license: cc0-1.0 |
| | task_categories: |
| | - video-classification |
| | tags: |
| | - zebra |
| | - giraffe |
| | - plains zebra |
| | - Grevy's zebra |
| | - video |
| | - animal behavior |
| | - behavior recognition |
| | - annotation |
| | - annotated video |
| | - conservation |
| | - drone |
| | - UAV |
| | - imbalanced |
| | - Kenya |
| | - Mpala Research Centre |
| | pretty_name: >- |
| | KABR: High-Quality Dataset for Kenyan Animal Behavior Recognition from Drone |
| | Videos |
| | size_categories: |
| | - 1M<n<10M |
| | --- |
| | # Dataset Card for KABR: High-Quality Dataset for Kenyan Animal Behavior Recognition from Drone Videos |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** https://dirtmaxim.github.io/kabr/ |
| | - **Repository:** https://github.com/dirtmaxim/kabr-tools |
| | - **Paper:** [Coming Soon] |
| | - **Leaderboard:** |
| | - **Point of Contact:** |
| |
|
| | ### Dataset Summary |
| |
|
| | We present a novel high-quality dataset for animal behavior recognition from drone videos. |
| | The dataset is focused on Kenyan wildlife and contains behaviors of giraffes, plains zebras, and Grevy's zebras. |
| | The dataset consists of more than 10 hours of annotated videos, and it includes eight different classes, encompassing seven types of animal behavior and an additional category for occluded instances. |
| | In the annotation process for this dataset, a team of 10 people was involved, with an expert zoologist overseeing the process. |
| | Each behavior was labeled based on its distinctive features, using a standardized set of criteria to ensure consistency and accuracy across the annotations. |
| | The dataset was collected using drones that flew over the animals in the [Mpala Research Centre](https://mpala.org/) in Kenya, providing high-quality video footage of the animal's natural behaviors. |
| |
|
| | <!--This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).--> |
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| | [Include Benchmarks Here] |
| |
|
| | ### Languages |
| |
|
| | [More Information Needed] |
| |
|
| | ## Dataset Structure |
| |
|
| | The KABR dataset follows the Charades format: |
| |
|
| | ``` |
| | KABR |
| | /images |
| | /video_1 |
| | /image_1.jpg |
| | /image_2.jpg |
| | ... |
| | /image_n.jpg |
| | /video_2 |
| | /image_1.jpg |
| | /image_2.jpg |
| | ... |
| | /image_n.jpg |
| | ... |
| | /video_n |
| | /image_1.jpg |
| | /image_2.jpg |
| | /image_3.jpg |
| | ... |
| | /image_n.jpg |
| | /annotation |
| | /classes.json |
| | /train.csv |
| | /val.csv |
| | ``` |
| |
|
| | The dataset can be directly loaded and processed by the [SlowFast](https://github.com/facebookresearch/SlowFast) framework. |
| |
|
| | **Informational Files** |
| | * `KABR/configs`: examples of SlowFast framework configs. |
| | * `KABR/annotation/distribution.xlsx`: distribution of classes for all videos. |
| |
|
| | **Scripts:** |
| | * `image2video.py`: Encode image sequences into the original video. |
| | * For example, `[image/G0067.1, image/G0067.2, ..., image/G0067.24]` will be encoded into `video/G0067.mp4`. |
| | * `image2visual.py`: Encode image sequences into the original video with corresponding annotations. |
| | * For example, `[image/G0067.1, image/G0067.2, ..., image/G0067.24]` will be encoded into `visual/G0067.mp4`. |
| |
|
| | ### Data Instances |
| |
|
| | [More Information Needed] |
| | **Naming:** Within the image folder, the `video_n` folders are named as follows (X indicates a number): |
| | * G0XXX.X - Giraffes |
| | * ZP0XXX.X - Plains Zebras |
| | * ZG0XXX.X - Grevy's Zebras |
| | * Within each of these folders the images are simply `X.jpg`. |
| |
|
| | ### Data Fields |
| |
|
| | [More Information Needed] |
| |
|
| | ### Data Splits |
| |
|
| | Training and validation sets are indicated by their respecive CSV files, located within the `annotation` folder. |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| |
|
| | We present a novel high-quality dataset for animal behavior recognition from drone videos. |
| | The dataset is focused on Kenyan wildlife and contains behaviors of giraffes, plains zebras, and Grevy's zebras. |
| | The dataset consists of more than 10 hours of annotated videos, and it includes eight different classes, encompassing seven types of animal behavior and an additional category for occluded instances. |
| | In the annotation process for this dataset, a team of 10 people was involved, with an expert zoologist overseeing the process. |
| | Each behavior was labeled based on its distinctive features, using a standardized set of criteria to ensure consistency and accuracy across the annotations. |
| | The dataset was collected using drones that flew over the animals in the [Mpala Research Centre](https://mpala.org/) in Kenya, providing high-quality video footage of the animal's natural behaviors. |
| | We believe that this dataset will be a valuable resource for researchers working on animal behavior recognition, as it provides a diverse and high-quality set of annotated videos that can be used for evaluating deep learning models. |
| | Additionally, the dataset can be used to study the behavior patterns of Kenyan animals and can help to inform conservation efforts and wildlife management strategies. |
| |
|
| | [To be added:] |
| | We provide a detailed description of the dataset and its annotation process, along with some initial experiments on the dataset using conventional deep learning models. |
| | The results demonstrate the effectiveness of the dataset for animal behavior recognition and highlight the potential for further research in this area. |
| |
|
| | ### Source Data |
| |
|
| | #### Initial Data Collection and Normalization |
| |
|
| | [More Information Needed] |
| |
|
| | Data was collected from 6 January 2023 through 21 January 2023 at the [Mpala Research Centre](https://mpala.org/) in Kenya. |
| |
|
| | #### Who are the source language producers? |
| |
|
| | [More Information Needed] |
| |
|
| | ### Annotations |
| |
|
| | #### Annotation process |
| |
|
| | [More Information Needed] |
| |
|
| | In the annotation process for this dataset, a team of 10 people was involved, with an expert zoologist overseeing the process. |
| | Each behavior was labeled based on its distinctive features, using a standardized set of criteria to ensure consistency and accuracy across the annotations. |
| |
|
| | #### Who are the annotators? |
| |
|
| | [More Information Needed] |
| |
|
| | ### Personal and Sensitive Information |
| |
|
| | [More Information Needed] |
| |
|
| | ## Considerations for Using the Data |
| |
|
| | ### Social Impact of Dataset |
| |
|
| | [More Information Needed] |
| |
|
| | ### Discussion of Biases |
| |
|
| | [More Information Needed] |
| |
|
| | ### Other Known Limitations |
| |
|
| | [More Information Needed] |
| |
|
| | ## Additional Information |
| |
|
| | ### Dataset Curators |
| |
|
| | [More Information Needed] |
| |
|
| | ### Licensing Information |
| |
|
| | [More Information Needed] |
| |
|
| | ### Citation Information |
| |
|
| | [More Information Needed] |
| |
|
| | ### Contributions |
| |
|
| | <!---location for authors instead of under curators?---> |
| | * Maksim Kholiavchenko (Rensselaer Polytechnic Institute) - ORCID: 0000-0001-6757-1957 |
| | * Jenna Kline (The Ohio State University) |
| | * Michelle Ramirez (The Ohio State University) |
| | * Sam Stevens (The Ohio State University) |
| | * Alec Sheets (The Ohio State University) - ORCID: 0000-0002-3737-1484 |
| | * Reshma Ramesh Babu (The Ohio State University) - ORCID: 0000-0002-2517-5347 |
| | * Namrata Banerji (The Ohio State University) - ORCID: 0000-0001-6813-0010 |
| | * Elizabeth Campolongo (Imageomics Institute) - ORCID: 0000-0003-0846-2413 |
| | * Nina Van Tiel (Eidgenössische Technische Hochschule Zürich) - ORCID: 0000-0001-6393-5629 |
| | * Jackson Miliko (Mpala Research Centre) |
| | * Eduardo Bessa (Universidade de Brasília) - ORCID: 0000-0003-0606-5860 |
| | * Tanya Berger-Wolf (The Ohio State University) - ORCID: 0000-0001-7610-1412 |
| | * Daniel Rubenstein (Princeton University) - ORCID: 0000-0001-9049-5219 |
| | * Charles Stewart (Rensselaer Polytechnic Institute) |
