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posted on 10.12.2021, 13:19 by Nitika NigamNitika Nigam, Deepali VermaDeepali Verma, Tanima Dutta
FallAction Dataset for Uncertain Action Recognition

Nitika Nigam, Deepali Verma, and Tanima Dutta
Indian Institute of Technology (BHU), India.

FallAction is an uncertain action recognition dataset of realistic people falling videos
collected from YouTube. The dataset comprises 15 fall action categories, and each
category contains 50-100 videos. FallAction gives the diversity in terms of different
falling actions and with the presence of noises, such as, variations in camera motions,
person appearance, viewpoint, cluttered background, illumination conditions, etc. It is a
challenging dataset for uncertain action recognition. Most action recognition datasets
are based on certain actions; on the contrary, FallAction aims to encourage further
research into uncertain action recognition by learning and exploring new realistic
uncertain fall action categories.
Structure for FallAction Dataset
● Data associated with each fall action category is stored in separate directories.
● Each directory comprises *.mp4 files for videos.
● The directory is arranged in the following structure:
├── Butt_fall
├── Drunk_fall
├── Elderly_fall
├── Escalator_fall
├── Faint_fall
├── False_start_fall
├── Handstand_fall
├── High_Heel_Break_fall
├── Karate_fall
├── Parkour_fall
├── Pool_fall
├── Side_fall
├── Surfing_fall
├── Trust_fall
└── Yoga_fall


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