## 4 The Proposed Method
### Fast Descriptor Matching
Finally, we have evaluated the SPFT on the several challenging datasets, and compared it with the state-of-the-arts feature tracking methods. Moreover, the SPFT is integrated into an SFM-based 3D reconstruction system, then resulting high-quality point-cloud models on the challenging datasets. I hold that the SPFT likes a unified framework of feature tracking, in which with different superpixel methods or KNN-like methods, the SPFT may produce a novel feature tracking method. Thus, the SPFT has good ex extendibility. Besides of promising feature tracking method, we have other valuable findings according to experiments: (1) the number of located keypoints largely depends on multiple scale spaces; (2) the context information is very important to construct a robust descriptor for keypoint; (3) the usage of shared memory in GPU device is also important to accelerate the feature matching speed. In summary, we proposed a promising feature tracking method for SFM-based 3D reconstruction, the quality of point-cloud model is significantly improved when it is used. In the future, we will try to propose a novel feature tracking method based on the proposed SPFT framework for simultaneous localization and mapping. Conceptualization, M.C. and L.Z. ; methodology, M.C. ; software, M.C. ; validation, M.C., W.J. and L.Z. ; formal analysis, Z.L. ; investigation, M.C. ; resources, W.J. ; data curation, M.C. ; writing--original draft preparation, M.C. ; writing--review and editing, Z.L., W.J. and X.L. ; visualization, M.C. ; supervision, X.L. ; project administration, L.Z. ; funding acquisition, X.L., M.C., W.J. and Z.L. This research was funded by [National Science Foundation of China] grant number [61802103, 61877016, and 61673157], and [Postdoctoral Science Foundation] grant number [2018M632522], and [Fundamental Research Funds for the Central Universities] grant number [JZ2018 HGBH0280, and PA2018 GDQT0014], and [Natural Science Foundation of Shandong Province] grant number [ZR2017 QF015], and [Key Research and Development Program in Anhui Province] grant number [1804a09020036]. The authors gratefully acknowledge the support of the National Natural Science Foundation (Grant No. : 61802103, 61877016, 61602146 and 61673157), Postdoctoral Science Foundation (Grant No. : 2018M632522), Fundamental Research Funds for the Central Universities (Grant No. : JZ2018 HGBH0280 and PA2018 GDQT0014), and Natural Science Foundation of Shandong Province (Grant No. : ZR2017 QF015), and Key Research and Development Program in Anhui Province (Grant No. : 1804a09020036). The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. ## References

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