# An Efficient Person Search Method Using Spatio-Temporal Features for Surveillance Videos +
## 4 Experiments and Results
### Experimental Results  
To evaluate search accuracy, we compared spatio-temporal features with spatial features in the framework of the proposed method. In order to compare them with spatio-temporal features, the bounding boxes of spatial features were also detected by the Yolov5 network, and the spatial features were extracted from key frames. As the number of bits in the hash code increased from 8 to 128, the MAP value of our method increased from 0.258 to 0.662 in Figure 4a, and the top-1 accuracy of our method increased from 0.377 to 0.897 in Figure 4b. This was because the large number of hash bits can increase the distinction between spatio-temporal features. Although the search accuracy of using only spatial features increases to some extent, it is still lower than the search accuracy of our method. Compared with the spatial features extracted from key frames, the spatio-temporal features not only contain the spatial features within each frame, but also represent the temporal relationship of spatial features between adjacent frames. The representative ability of spatio-temporal features is better than that of spatial features, thereby increasing the distinction between different persons in the surveillance videos. Thus, the search accuracy is improved by utilizing the spatio-temporal features. To further verify the effectiveness of the proposed method, our method was compared with RCNN, which is also employed to generate spatio-temporal features. In the structure of RCNN, the pedestrian proposal net is used to select the top 128 bounding boxes, and the identification net is used to extract spatial features. For the same comparison with our method, these spatial features were also fed into GRU to generate 256-dimensional spatio-temporal features, and then organized by LSH. As the number of bits in the hash code increases, the MAP value of our method is larger than that of RCNN in Figure 5a, and the top-1 accuracy of our method is also better in Figure 5b. This is because the pedestrian proposal net in RCNN would inevitably generate some false alarms and misalignments in the bounding boxes, which reduce the representative ability of spatio-temporal features and decrease the search accuracy. Compared with RCNN, the Yolo network used in our method can avoid the false alarms in the candidate bounding boxes and provide fast detection speed for a large number of frames. Therefore, the search accuracy of our method is improved by combining the Yolo network with GRU. Figure 4: The accuracy comparison between spatio-temporal features and spatial features: (**a**) MAP comparison; (**b**) Top-1 accuracy comparison. To further evaluate search accuracy, accuracy comparison was performed between GRU and LSTM with different pooling methods. In Figure 6, as the number of bits in the hash code increases, the search accuracy of four different methods increases. However, with the same pooling method, the search accuracy of GRU is better than that of LSTM. This is because GRU can be trained more easily and effectively than LSTM, and the parameters of GRU are fewer. Thus, GRU can better calculate the temporal correlation of the same person between adjacent frames and achieves better performance than LSTM in the search process. On the other hand, when using GRU or LSTM in the same situation, the search accuracy of the average pooling method is also better than that of the max pooling method, as shown in Figure 6. Compared with the max pooling method, the average pooling method can generate more representative spatio-temporal features. Of the four different methods, GRU and the average pooling method achieve the largest search accuracy. Therefore, in our proposed method, we employ GRU and the average pooling method to increase search accuracy. Figure 5: The accuracy comparison between our method and RCNN method using spatio-temporal features: (**a**) MAP comparison; (**b**) Top-1 accuracy comparison.