Abstract:In order to solve the problem that traditional technology is susceptible to external disturbance, resulting in the absence of visual features, affecting the localization results, and can only be applied to visual feature localization with significant color features, a large area campus intelligent visual feature localization technology based on Internet of Things (IOT) is studied by SURF and Euler distance matching. Intelligent acquisition of the campus image of the large area monitored by the Internet of Things (IOT) technology is carried out, and the distribution of the IOT vision sensor is given. Preprocessing the acquired images to enhance the ability of image interference suppression. The image is regarded as a packet, and the segmented image block is regarded as an example in the packet to determine the optimal labeling for a visual image in a large area. On this basis, SURF algorithm is used to detect the visual feature points, and Euler distance is used to realize the intelligent visual feature matching and location of large regional college under the Internet of Things. The results show that there is no significant difference in the detection characteristics of the proposed technology, and the positioning error is low for the daytime campus sidewalk area, and no significant difference is found for the night campus main road area. It can be seen that the positioning accuracy of the proposed technology is high.