Image Segmentation and Target Extraction of Preschool Educational Activity Space for Improving Children's Concentration

Abstract

Concentration is crucial for children to nurture good personality and develop well. To observe teachers and children in concentration-oriented preschool education activities, it is necessary to analyze the video images of relevant activities. This paper the image segmentation and target extraction of preschool education activity space for improving children's concentration. After discussing the relationship between children's concentration and preschool educational activity intervention, the authors introduced the frequency-tuned saliency algorithm into the constructed Gaussian mixture model, constructed the spatial information of the images on the preschool educational activity space for improving children's concentration, and successfully segmented these images. Since the target children are small and numerous, have color overlap with the background, and face strong light interference, the ViBe algorithm with complex scenes, i.e., ViBe+, was selected to quickly detect the multiple child targets in complex preschool education activity environments. Experimental results verify the effectiveness of the proposed algorithm.