A Novel Image Descriptor With Aggregated Semantic Skeleton Representation For Long-Term Visual Place Recognition : 0xbt

A Novel Image Descriptor With Aggregated Semantic Skeleton Representation For Long-Term Visual Place Recognition

Coffee to go! cafe characterdesign coffee coffeebrand coffeelogo coffeeshop cute cute art design illustrationMoreover, SSR-VLAD achieves comparable efficiency with Net-VLAD, which is a network specially educated for VPR process. Therefore, we can find that SSR-VLAD, which are extracted based mostly on semantic segmentation, could be utilized to the VPR task of urban scenes with modifications in appearance, and can achieve the SoTA performance. Figure 2: Experiment end result on the evaluated long-term city datasets. Fig2-Fig2 show the PR-curve of all evaluated strategies in three datasets. Fig2-Fig2 show the comparability of the AUC values of all evaluated strategies in three datasets. The computational price of a VPR algorithm at run-time is also an essential metric for evaluating. The results of computational cost experiments are shown in TableIII. For the reason that CoHOG algorithm generates descriptors while extracting options, for CoHOG we merge the time-consuming strategy of feature extraction and descriptor encoding. The reason being that the computing power of the experimental platform used in this paper is far decrease than theirs and when the code is working, all cores of the CUP of the experimental platform are working at full capacity.

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