The person detection and tracking integration technology has important application in many fields. Its key technology include: robust target detection and path correlation technology. The mainstream path correlation technology only considers the time correlation of the target, and does not take into account their spatial-temporal association property. When similar targets are too close, it is easy to lead to misalignment tracking. This paper proposes an integrated method of target detection and tracking based on deep neural network learning and structured online learning algorithm. The method can establish the target spatial-temporal relationship by constructing a structured online learning model. Experimental results show that the proposed method has resisted the interference problem of similar targets, and improved the ability of resisting serious occlusion.