In recent years, the intelligence of various parts of the home has become one of the essential features of any modern home. One of these parts is the intelligence lighting system that personalizes the light for each person. This paper proposes an intelligent system based on machine learning that personalizes lighting in the instant future location of a recognized user, inferred by trajectory prediction. Our proposed system consists of the following modules: (I) human detection to detect and localize the person in each given video frame, (II) face recognition to identify the detected person, (III) human tracking to track the person in the sequence of video frames and (IV) trajectory prediction to forecast the future location of the user in the environment using Inverse Reinforcement Learning. The proposed method provides a unique profile for each person, including specifications, face images, and custom lighting settings. This profile is used in the lighting adjustment process. Unlike other methods that consider constant lighting for every person, our system can apply each 'person's desired lighting in terms of color and light intensity without direct user intervention. Therefore, the lighting is adjusted with higher speed and better efficiency. In addition, the predicted trajectory path makes the proposed system apply the desired lighting, creating more pleasant and comfortable conditions for the home residents. In the experimental results, the system applied the desired lighting in an average time of 1.4 seconds from the moment of entry, as well as a performance of 22.1mAp in human detection, 95.12% accuracy in face recognition, 93.3% MDP in human tracking, and 10.80 MinADE20, 18.55 MinFDE20, 15.8 MinADE5 and 30.50 MinFDE5 in trajectory prediction.
翻译:近年来,智能家居各个部分的智能化已成为任何现代家庭的重要特征之一。其中之一便是智能照明系统,该系统为每个人个性化定制灯光。本文提出了一种基于机器学习的智能系统,通过轨迹预测来个性化定制即时环境中已认证用户的照明。我们提出的系统包含以下模块:(I)人体检测,用于检测和定位给定视频帧中的人体,(II)人脸识别,用于识别检测到的人体,(III)人体跟踪,用于在视频帧序列中跟踪人体,和(IV)轨迹预测,使用反强化学习预测用户在环境中的未来位置。所提出的方法为每个人提供了一个独特的配置文件,包括规格、面部图像和自定义照明设置。该配置文件在照明调整过程中被使用。与其他方法考虑为每个人提供恒定的照明不同,我们的系统可以为每个人应用所需的照明,包括颜色和灯光强度,而无需直接用户干预。因此,调整照明更加快速和高效。此外,预测的轨迹路径使所提出的系统可以应用所需的照明,为家庭居民创造更舒适、宜人的条件。在实验结果中,系统在进入照明调整的平均时间为1.4秒,人体检测性能为22.1mAp,面部识别准确率为95.12%,人体跟踪MDP为93.3%,轨迹预测MinADE20为10.80分、MinFDE20为18.55分、MinADE5为15.8分、MinFDE5为30.50分。