RIS Based Hand Gesture Recognition Dataset

This dataset contains images for gesture recognition, divided into two main sets: dataset0608 and data_synthetic_variab. The data was collected using a wooden hand.

dataset0608 This dataset consists of two modes: ris_random and ris_optimized. The main difference between the two subfolders is the configuration of the RIS (random or optimized).

This dataset consists of four subfolders: ris_random, ris_random2, ris_optimized, and ris_optimized2. The main difference between the subfolders is the format of the data: - ris_random and ris_optimized: Data is stored in individual files for each frame, named as 'frame_{i}{posture}{n_med}' - ris_random2 and ris_optimized2: Data has already been processed and combined into single files for all frames using the compact_files_frames.txt function, named as 'all_frames_{posture}_{n_med}'

For each gestures = {close, two, open}, we have n_med values from 0 to 114 and 10 frames. Therefore, the ris_random and ris_optimized folders contain 10 frames × 115 measurements × 3 gestures = 3450 files, while the ris_random2 and ris_optimized2 folders contain 1 × 115 measurements × 3 gestures = 345 files.

data_synthetic_variab

This dataset consists of two modes: ris_random and ris_optimized. The main difference between the two subfolders is the configuration of the RIS (random or optimized).

This dataset consists of four subfolders: ris_random, ris_random2, ris_optimized, and ris_optimized2. The main difference between the subfolders is the format of the data: - ris_random and ris_optimized: Data is stored in individual files for each frame, named as 'frame_{i}{posture}{n_med}' - ris_random2 and ris_optimized2: Data has already been processed and combined into single files for all frames using the compact_files_frames.txt function, named as 'all_frames_{posture}_{n_med}'

For each gestures = {close, two, open}, we have n_med values from 0 to 8 and 10 frames. This dataset provides additional synthetic data with variations in hand position to increase the dataset's diversity. Each gesture is represented by 8 different ways, where the hand position was slightly modified between each sample. These real data were used as a basis for generating synthetic data. By using the functions in the files "multiply_files.txt" and "add_gaussian_noise.txt," the dataset was expanded and made more realistic by adding Gaussian noise to the images.

Therefore, the ris_random and ris_optimized folders contain 10 frames × 8 measurements × 3 gestures = 240 files, while the ris_random2 and ris_optimized2 folders contain 1 × 8 measurements × 3 gestures = 24 files.

Functions * add_gaussian_noise.txt: This script adds Gaussian noise to the images to simulate real-world conditions and improve the robustness of the model. * compact_files_frames.txt: This script combines multiple frames into a single image, which can be useful for certain types of analysis.

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추가 정보

필드
저자 Mariana Barros Oliveira, Francisco M. Ribeiro, Nuno Paulino, Luís M. Pessoa
최종 업데이트 9월 24, 2024, 10:29 (UTC)
생성됨 9월 24, 2024, 10:16 (UTC)
Citation Oliveira, M., Ribeiro, F. M., Paulino, N., & Pessoa, L. M. (2024). RIS Based Hand Gesture Recognition Dataset [Data set]. INESC TEC. https://doi.org/10.5281/zenodo.13754235
DOI 10.5281/zenodo.13754234