Hajj and Umrah Event Recognition Datasets
This provides a new dataset for researchers in computer vision and event recognition focusing on Hajj and Umrah rituals, but it is incremental as it primarily offers new data without novel methods.
The authors introduced the Hajj and Umrah Event Recognition (HUER) datasets, the first collection covering six ritual events and nine human actions from videos and images taken during the 2011-2012 seasons, with spatial resolutions of 1280x720 pixels for images and 640x480 pixels for videos averaging 20 seconds at 30 fps.
In this note, new Hajj and Umrah Event Recognition datasets (HUER) are presented. The demonstrated datasets are based on videos and images taken during 2011-2012 Hajj and Umrah seasons. HUER is the first collection of datasets covering the six types of Hajj and Umrah ritual events (rotating in Tawaf around Kabaa, performing Sa'y between Safa and Marwa, standing on the mount of Arafat, staying overnight in Muzdalifah, staying two or three days in Mina, and throwing Jamarat). The HUER datasets also contain video and image databases for nine types of human actions during Hajj and Umrah (walking, drinking from Zamzam water, sleeping, smiling, eating, praying, sitting, shaving hairs and ablutions, reading the holy Quran and making duaa). The spatial resolutions are 1280 x 720 pixels for images and 640 x 480 pixels for videos and have lengths of 20 seconds in average with 30 frame per second rates.