Maneuvering target recognition method based on multi-perspective light field reconstruction

Abstract

It is difficult to reconstruct the complete light field, and the reconstructed light field can only recognize specific fixed targets. These have limited the applications of the light field in practice. To solve the problems above, this article introduces the multi-perspective distributed information fusion into light field reconstruction to monitor and recognize the maneuvering targets. First, the light field is represented as sub-light fields at different perspectives (i.e. the Multi-sensor distributed network), and sparse representation and reconstruction are then performed. Second, we establish the multi-perspective distributed information fusion under the condition of regional full-coverage constraints. Finally, the light field data from multiple perspectives are fused and the states of the maneuvering targets are estimated. Experimental results show that the light field reconstruction time of the proposed method is less than 583 s, and the reconstruction accuracy exceeds 92.447% compared with the existing spatially variable bidirectional reflectance distribution function, micro-lens array, and others. In the aspect of maneuvering target recognition, the recognition time of the algorithm in this article is no more than 3.5 s. The recognition accuracy of the algorithm in this article is up to 86.739%. Moreover, the more viewing angles used, the higher the accuracy.

Multiagent Light Field Reconstruction and Maneuvering Target Recognition via GAN

“…In Figure 6 and Table 1, we can clearly see the comparison between the reconstruction time and the reconstruction accuracy of the proposed algorithm and various comparison algorithms. In the Lego Truck dataset, due to the complex structure of the reconstruction part, the reconstruction time of ours took 18 seconds more than the literature [3]. However, the reconstruction accuracy rate is 92.613%, which is the highest among similar algorithms.…”

“…Literature [3] Literature [23] Literature [24] Literature [26] Ours Figure 6: Light field reconstruction results.…”

“…Test. e data for this experiment are from the Stanford University Square database and are compared with the existing algorithms in Literature [3], Literature [23], Literature [24], and Literature [26] reconstruction results.…”

“…e visual range of the complete light field is limited, and the target may be lost due to the interference of blurring and occlusion. Cai et al [3] proposed a target recognition method based on multiperspective reconstruction, through which the light field data from multiple perspectives are fused and the consistency of the average of all observations is obtained.…”

Multiperspective Light Field Reconstruction Method via Transfer Reinforcement Learning

“…Many researchers have proposed the concept of light field reconstruction, using the sparsity of the light field to reconstruct the unknown information of the targets from locally known information. Cai et al [15] proposed a target recognition method based on multiperspective reconstruction, through which the light field data from multiple perspectives are fused and the consistency of the average of all observations is obtained.…”