Gait Energy Image Generation from Image Sequences

Generate gait energy images by inputting the starting frame number of image sequences. To obtain more accurate gait energy images, image preprocessing can be performed before processing, such as noise removal and contrast enhancement using techniques like Gaussian filtering or histogram equalization. Additionally, various feature extraction algorithms can be employed to extract key information from image sequences, including joint angles, movement velocity, and spatial-temporal patterns through optical flow computation or skeleton tracking. After obtaining the gait energy image, further analysis and processing can be conducted based on different application requirements, such as walking posture recognition using pattern classification algorithms or abnormal behavior detection through anomaly detection models. In summary, through systematic processing and analysis of image sequences, we can acquire detailed gait information and provide more possibilities for related applications like biometric identification, medical diagnosis, and sports analytics.