现代家居空间中的多目标智能定位系统设计应用研究

Research on the design and application of multi-objective intelligent positioning system in modern home space

为提高现代家居空间设计效果和多目标定位识别能力,提出一种基于三维像素特征重建的现代家居空间中的多目标智能定位系统设计方法。采用图像识别技术进行现代家居空间的图像特征采样,对采集的现代家居空间图像进行三维数据场模拟,结合帧差异性扫描技术进行现代家居空间中的多目标特征提取,采用三维模板匹配实现现代家居空间多目标图像重建,提高对现代家居空间多目标图像重构图像的统计信息特征表达能力,根据统计特征提取结果,进行多目标智能定位识别。在算法设计的基础上,在嵌入式Linux环境中进行现代家居空间中的多目标智能定位系统的硬件集成设计,采用低功耗的模式识别方法进行现代家居空间中的多目标智能定位系统的智能视觉图像识别,在人机交互界面中进行定位识别输出显示。仿真结果表明,采用该方法进行现代家居空间中的多目标智能定位的准确性较高,抗干扰能力较强,提高了图像识别准确性。

In order to improve the ability of target location recognition in modern home space,a design method of multi-objective intelligent positioning system in modern home space based on 3 D pixel feature reconstruction is proposed. Image recognition technology is used to sample the image features of modern home space,3 D data field simulation is carried out on the collected modern home space image,and multi-target feature extraction from modern home space is carried out by combining frame difference scanning technology. The 3 D template matching is used to reconstruct the multi-object image of modern home space,and the ability of expressing the statistical information of the reconstructed image is improved. According to the result of the statistical feature extraction,the multi-target intelligent location recognition is carried out. Based on the algorithm design,the hardware integration design of the multi-objective intelligent positioning system in the modern home space is carried out in the embedded Linux environment. The low power consumption pattern recognition method is used to recognize the intelligent visual image of the multi-object intelligent positioning system in the modern home space,and the location recognition output is displayed in the man-machine interface. The simulation results show that this method has high accuracy and strong anti-interference ability for multi-target intelligent positioning in modern home space,and improves the accuracy of image recognition.