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Fitness

Occlusion Dataset

A synthetic vision dataset for fitness featuring complex and diverse patterns of avatar occlusion.

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The Fitness Occlusion Dataset focuses on various challenging occlusion patterns within the home fitness and physical therapy context. The dataset includes videos of 4 different exercises being performed by avatars that are occluded by miscellaneous objects in the foreground. Objects were carefully chosen to introduce complex spatial patterns of occlusion. For each exercise, the amount of occlusion is curated to be roughly uniform between 5 and 60% across videos.


KEY FEATURES

<ul>
<li>200 videos spanning 4 exercises</li>
<li>Varying amounts of avatar occlusion (roughly uniform between 5-60% per exercise)</li>
<li>No out-of-frame avatars</li>
<li>7-14 reps per video</li>
<li>30 FPS data, 512x512 resolution videos</li>
<li>Avatars with diverse heights and body shapes</li>
<li>Variation in kinematic trajectories and exercise speeds</li>
<li>3 interior environments</li>
</ul>

EXERCISES

The dataset includes the following exercises:
<ol>
<li>Situps</li>
<li>Overhead press (one-arm)</li>
<li>Sumo squat </li>
<li>Split squat</li>
</ol>

ANNOTATIONS

Each video is accompanied by a rich set of pixel-perfect labels and annotations, including:
<ul>
<li>Per-frame and average occlusion %</li>
<li>Segmentation masks and bounding boxes for avatars and dumbbells</li>
<li>Frame-specific rep counts</li>
<li>Avatar characteristics (gender, clothing, waist circumference, etc.)</li>
<li>Camera location</li>
<li>2D and 3D skeleton keypoints</li>
<li>Depth maps available upon request </li>
<li>And much more!</li>
</ul>
For the full description of labels and metadata, check out the <a href="https://github.com/toinfinityai/infinity-datasets/tree/main/fitness-occlusion" target="_blank">README</a>.

FILE SIZE

512 x 512 mp4 videos (30 FPS).
<br>
Total size: 2.5 GB
<br>
Each exercise is in a different zipped folder (250-800 MB)

LICENSE

The API and the synthetic data generated by the API are licensed under Infinity AI’s <a href="https://infinity.ai/terms" target="_blank">Terms and Conditions</a>.

RESOURCES

<ul>
<li>Github <a href="https://github.com/toinfinityai/infinity-datasets/tree/main/fitness-occlusion" target="_blank">README</a>: full dataset and annotation descriptions.</li>
</ul>

Questions? We’re happy to chat asynchronously via email or hop on a call. Just send us a note at info@infinity.ai (this goes to all of the Infinity AI founders).

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