# Research on an Optimal Path Planning Method Based on A* Algorithm for Multi-View Recognition
## 4 Experimental Verification and Analysis
### Optimization Path Planning for Multi-View Recognition
#### 4.3.2 Path Planning with Different Starting Points  
Different starting points are selected to determine the optimal viewpoint path planning. The top views of the observation models are shown in Figures 12-14. Figure 12 shows the optimal path when the number of viewing angles is three. The starting point of the red real line track is \(\Phi_{11}\), the starting point of the green dotted line track is \(\Phi_{(11)2}\), and the starting point of the blue dotted line track is \(\Phi_{(25)3}\).  
Figure 13 is the optimal path with viewing angles = 4, Figure 14 is the optimal path with viewing angles = 5, and the color and track starting point is consistent with Figure 12. By comparing the three figures, it can be seen that the planned path can quickly reach the better viewing point. With the bottom as the benchmark, the longitude direction is about 50\({}^{\circ}\), and then the trend is mainly planned along the latitude direction. When the angle of view is 3, the path planning can complete the identification of two sides and top surfaces. Increasing the viewpoint angles, the movement is mainly along the latitude direction. It can be concluded that this method can well complete the viewpoint optimization path planning under different starting points and different viewing angle constraints in the barrier free environment, and effectively complete the optimal balance between recognition performance and search speed.  
The performance of target recognition is compared with different starting viewpoints and different viewing angles. When the number of viewing angles is 3, the recognition accuracy of different starting viewpoints is shown in Table 1. The data is the identification  
Figure 14: Five-view optimal observation paths.  
Figure 13: Four-view optimal observation paths.  
It can be seen from the Figure 15 that the recognition accuracy has a gradual downward trend, tending to the vertex of the hemisphere of the starting point. The starting point is at the 8 th and 9 th layers of longitude especially, because the set directed graph model is in a single direction. The more it tends to the vertex, the less the observation surface is, and the less the extracted features are. Even if the perspective is increased, the increase in recognition effect is not obvious due to the particularity of its location. Therefore, in practical application, try to avoid a starting point close to the top position. However, on the whole, the average recognition rate is 91.51% in the case of three viewing angles, 92.25% in the case of four viewing angles and 93.13% in the case of five viewing angles. The results show that the more viewing angles, the higher the target recognition rate. This method can obtain a higher recognition rate in an obstacle-free environment.  
Through the above experimental analysis, it can be concluded that the proposed directed graph perspective optimization path planning method based on the A* algorithm considering the performance and efficiency of target recognition is feasible, and can obtain more accurate recognition results in a shorter path.