Hand-Gesture Recognition

The IPN Hand dataset is a benchmark video dataset with sufficient size, variation, and real-world elements able to train and evaluate deep neural networks for continuous Hand Gesture Recognition (HGR). Source: https://github.com/GibranBenitez/IPN-hand

The VIVA challenge’s dataset is a multimodal dynamic hand gesture dataset specifically designed with difficult settings of cluttered background, volatile illumination, and frequent occlusion for studying natural human activities in real-world driving settings. This dataset was captured using a Microsoft Kinect device, and contains 885 intensity and depth video sequences of 19 different dynamic hand gestures performed by 8 subjects inside a vehicle. Source: Short-Term Temporal Convolutional Networks for Dynamic Hand Gesture Recognition Image Source: http://www.site.uottawa.ca/research/viva/projects/hand_detection/index.html

Contains static tasks as well as a multitude of more dynamic tasks, involving larger motion of the hands. The dataset has 55 tremor patient recordings together with: associated ground truth accelerometer data from the most affected hand, RGB video data, and aligned depth data. Source: Hand-tremor frequency estimation in videos

MlGesture is a dataset for hand gesture recognition tasks, recorded in a car with 5 different sensor types at two different viewpoints. The dataset contains over 1300 hand gesture videos from 24 participants and features 9 different hand gesture symbols. One sensor cluster with five different cameras is mounted in front of the driver in the center of the dashboard. A second sensor cluster is mounted on the ceiling looking straight down. Source: MLGESTURE DATASET

The dataset consists of images of Human palms captured using a mobile phone. The images have been taken in a real-world scenario like holding objects or performing simple gestures. The dataset has a wide variety of variations like illumination, distances etc. It consists of images of 3 main gestures: Frontal-open palm, Back open palm and fist with the wrist. It also has a lot of images with people wearing gloves. Dataset Features: - Captured by 4000+ unique users - Covers wide variety of palm images in indoor and outdoor scenes - Images of palm with gloves - Captured by male and female - Distributed age groups like teenage, adults and old - Captured using mobile phones - Highly diverse - Various lighting conditions like day, night, indoor and outdoor - Outdoor scene with a variety of viewpoints Annotations Format: - Classification and detection annotations available - Multiple category annotations possible - COCO, PASCAL VOC and YOLO formats To download full datasets or to submit a request for your dataset needs, please ping us at (sales@datacluster.ai)[sales@datacluster.ai] Visit www.datacluster.ai to know more.