graviti logo产品公开数据集关于我们
Demo演示登录
738
0
19
Fall detection
概要
讨论
代码
活动
33c77c27-8ce2-11eb-b816-506b4b419b4c
6732dfa·
Jun 28, 2021 12:08 AM
·1Commits

Overview

The datasets that are used for the simulation purpose are raw RGB and Depth images of size 320x240 recorded from a single uncalibrated Kinect sensor after resizing from 640x480. The Kinect sensor is fixed at roof height of approx 2.4m. The datasets contain a total of 21499 images. Out of total datasets of 22636 images, 16794 images can be used for training, 3299 images can be used for validation and 2543 images can be used for the test. The images in the dataset are ecorded in 5 different rooms which consist of 8 different view angles. There are 5 different participants out of which there are two male participants of age 32 and 50 and three female participants of age 19, 28 and 40. All the activities of the participants represent 5 different categories of poses that are standing, sitting, lying, bending and crawling. There is only one participant in each image. Some images in the datasets are empty which are categorised as 'other'. We have used images of 2 participants: the male of age 32 and the female of age 28 combining total of 16794 images for training, and 3299 images for validation which contains a male participant of age 32 from training set but is in a different room to that of training and testing set. Similarly, the test set contains images of 3 participants out of which 2 female participants are of age 19 and 40 and a male participant is of age 50. These images are recorded in a different room that is not seen in training or validation set. These total of 22636 images are in sequence but have not repeated anywhere in the sequence and all the sets have original and its horizontal flipped images added in sequence to increase the number of images in a set.

Format

Posses and labels:

Standing: class 1, Sitting: class 2, Lying: class 3, Bending: class 4, Crawling: class 5, Empty: class 0

Label format (CSV):

Serial numberClass
14
23
30
42
51
65

Instruction

Train Dataset(RGB+Depth+Label)Validate Dataset(RGB+Depth+Label)Test Dataset(RGB+Depth+Label)
13011176832
17902123786
722925
1378
1392
807
758
1843
569
1260
489
731
1219
1954
581
Total:16794Total:3299Total:2543

Citation

@INPROCEEDINGS{7986795,
    author={K. {Adhikari} and H. {Bouchachia} and H. {Nait-Charif}},
    booktitle={2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)},
    title={Activity recognition for indoor fall detection using convolutional neural network},
    year={2017},
    volume={},
    number={},
    pages={81-84},
    doi={10.23919/MVA.2017.7986795}
}
🎉感谢Hello Dataset的贡献
数据集信息
应用场景暂无
标注类型暂无
任务类型暂无
LicenseCustom
更新时间2021-01-22 10:51:49
数据概要
数据格式暂无
数据数量0
已标注数量0
文件大小7MB
版权归属方
The International Association for Pattern Recognition
标注方
未知
了解更多和支持
立即开始构建AI
免费开始联系我们