Comparing with other methods on the Le2i Fall detection Dataset (LFDD) to verify the effectiveness of the AT-MLP model, the experimental results show that the AT-MLP model effectively improves the detection efficiency of human falls and has strong generalization ability.Huan Zhang...
An iOS fall detection data collection system. It uses CoreMotion for retrieving accelerometer, magnetometer, and gyroscope sensors, and interfaces with a PolarH10 chest strap for ECG data using the Polar SDK. - hwixley/Fall-Detection-Dataset-Generator
Fall detection Dataset 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 ...
dataset_preprocessing .gitignore LICENSE README.md brightness.py requirements.txt temporalnet_combined.py temporalnet_fdd.py temporalnet_multicam.py temporalnet_urfd.py README MIT license Fall-Detection-with-CNNs-and-Optical-Flow This repository contains the code for our paper: ...
Lastly, we build a multi-person fall detection dataset (MPFDD) to test the model's effectiveness in multi-person scenarios. Validated on datasets Le2i and MPFDD, our method improves accuracy by 4.30%, F1 by 4.57%, and FPS by 37.50% faster than the AlphaPose. Compared with other models,...
The utils.py file contains utility code for generating the data, the train_model.py file creates and trains the model, and the fall_detection.py file contains code that runs the model with the weight in the weights folder either on the FDD dataset, a video, or your webcam. More ...
3.3. FallDetection DATASET (FDD) This dataset was recorded with a single uncalibrated Kinect sensor and resized at 320 × 240—the original size was 640 × 480. They collected 21,499 images in total and divided them into training and testing. The total number of images in the training datas...
4.1. Dataset FDD (fall detection dataset) [35] is a public dataset for vision-based fall recognition. It contains 191 videos with a rate of 25 FPS and a resolution of 320 × 240 pixels. The 191 videos of different lengths include various fall actions and ADL actions of different people ...
3.1. Dataset The Fall Detection Dataset (FDD) [53] is used to conduct the experiments. The dataset consists of 124 annotated RGB videos comprising 94 falls and 30 ADLs videos in two different simulated situations, termed as the “Coffee Room” and “Home” situation as shown in Figure 3. ...
Our experimental dataset called “Postures of Fall (PoF)” is different from existing fall datasets, such as the University of Rzeszow fall detection dataset (URFD) and the fall detection dataset (FDD) [23] and Multi-cam [19] in the indoor scenes. The comparison of these datasets and the ...