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This article proposes a robust image-sequence-based framework to deal with two challenges of visual place recognition in changing environments: 1) viewpoint variations and 2) environmental condition variations. Our framework includes two main parts. The first part is to calculate the distance between two images from a reference image sequence and a query image sequence. In this part, we remove the deep features of nonoverlap contents in these two images and utilize the remaining deep features to calculate the distance. As the deep features of nonoverlap contents are caused by viewpoint variations, removing these deep features can improve the robustness to viewpoint variations. Based on the first part, in the second part, we first calculate the distances of all pairs of images from a reference image sequence and a query image sequence, and obtain a distance matrix. Afterward, we design two convolutional operators to retrieve the distance submatrix with the minimum diagonal distribution. The minimum diagonal distribution contains more environmental information, which is insensitive to environmental condition variations. The experimental results suggest that our framework exhibits better performance than several state-of-the-art methods. Moreover, the analysis of runtime shows that our framework has the potential to satisfy real-time demands.
This article was published in the following journal.
Name: IEEE transactions on cybernetics
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A visual image which is recalled in accurate detail. It is a sort of projection of an image on a mental screen.
The selecting and organizing of visual stimuli based on the individual's past experience.
The analysis of a critical number of sensory stimuli or facts (the pattern) by physiological processes such as vision (PATTERN RECOGNITION, VISUAL), touch, or hearing.
The deletion and reinsertion of a segment of a nucleic acid sequence in the same place, but flipped in an opposite orientation.
A family of RNA-BINDING PROTEINS that contain an RNA RECOGNITION MOTIF and two ribonucleoprotein (RNP) domains which bind RNA, in addition to other domains that allow for high affinity binding, sequence specificity, and protein interactions. Examples of RNA recognition motif proteins include HETEROGENEOUS NUCLEAR RIBONUCLEARPROTEINS (hnRNP) and EMBRYONIC LETHAL ABNORMAL-VISION (ELAV) proteins.
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