Dataset for "Adaptive Keyframe Selection for Indoor Positioning Using Controllable Kernel Density Estimation"

This dataset supports the article <i>"Adaptive Keyframe Selection for Indoor Positioning Using Controllable Kernel Density Estimation"</i>. The dataset includes RGB image frames captured from various indoor environments, organized into folders by scene or location (e.g., corridors, staircases). Each folder contains frames extracted from video sequences and is optionally aligned with associated RSS (Wi-Fi signal strength) values. These data were used for evaluating the proposed CKDE framework for keyframe extraction that combines visual and RSS-based information to improve indoor positioning robustness.The dataset may include:Raw or preprocessed image framesOptional corresponding metadata (e.g., RSS values per frame or location)README file explaining folder structure, preprocessing steps, and formatThis dataset was collected at Ferdowsi University of Mashhad (Engineering Faculty) and is used in experiments described in Section 5 of the paper.

本数据集支撑学术论文《自适应可控核密度估计的室内定位关键帧选择》（Adaptive Keyframe Selection for Indoor Positioning Using Controllable Kernel Density Estimation）。该数据集涵盖从多种室内环境采集的RGB图像帧，按场景或地点（如走廊、楼梯间）划分为不同文件夹。每个文件夹内存储有从对应视频序列中提取的图像帧，且可选择性地配套关联相关RSS（Wi-Fi信号强度）数据。上述数据被用于评估所提出的CKDE（可控核密度估计，Controllable Kernel Density Estimation）关键帧提取框架，该框架结合视觉信息与基于RSS的特征信息，以提升室内定位的鲁棒性。本数据集可包含：原始或预处理后的图像帧、可选的配套元数据（如每帧或对应地点的RSS值），以及用于说明文件夹结构、预处理步骤与数据格式的README文件。本数据集采集于马什哈德费尔多西大学工程学院，用于该论文第5章节所述的实验研究。