Application of imaging detection based on spatial optical characteristics in motion attitude recognition

Abstract

Abstract Space optical imaging technology has a wide range of applications in motion attitude recognition, but due to changes in optical characteristics during motion, the accuracy and efficiency of imaging detection still face challenges. This article proposes a new imaging detection method based on spatial optical characteristics to improve the accuracy and efficiency of motion pose recognition. Firstly, a detailed analysis was conducted on the changes in optical characteristics of moving objects. Based on the research on the changes in optical characteristics, an imaging detection algorithm based on spatial optical characteristics was designed. This algorithm utilizes image processing and pattern recognition techniques to extract key features from the imaging process. Subsequently, feature extraction techniques are used to extract key features related to motion posture from the preprocessed images. Using pose matching algorithms, based on known pose feature models and extracted key features, the pose of a moving object is determined by calculating similarity. Compared with traditional methods, this method exhibits better performance in accuracy and efficiency, and can accurately recognize the posture of moving objects in complex motion scenes, providing technical support for research and application in the field of motion posture recognition.