Video tracking technology based on shoe patterns is commonly used by public security organizations in criminal investigations and is crucial in actual public security combat. However, this technology relies heavily on manual screening with a heavy workload and low efficiency, and it is prone to missed inspections. In view of this, an automatic shoe detection algorithm based on Single Shot MultiBox Detector (SSD) model is proposed herein to achieve automatic detection and positioning of pedestrian shoes. First, the structure of the SSD model and the parameters of the prior frame are designed to meet the practical application of shoe detection. Then, the method for adjusting network parameters is used to improve the detection performance and stability of the network and the network model and method suitable for shoe detection are improved. Thus, an accurate and efficient single-category shoe detection network is obtained. Finally, performance evaluation in the shoe sample database constructed by the research group in the early stage is conducted. Experimental results show that the average accuracy of the proposed algorithm is 0.891.