Exploiting Structural Knowledge for Place Recognition
Place recognition is the problem of finding associations between a query set of place descriptions and a database. It is an important means for loop closure detection in SLAM. The primary source of information to decide about associations is the pairwise similarity of descriptors between the query and the database items (e.g., image descriptor similarities). Beyond better descriptors, significant improvements were achieved by exploiting additional structural information, in particular by comparing sequences instead of individual items. We work towards exploitation of additional systematic sources of information. For example, intra-set similarities between items within the query or the database sets. They can be used to detect inconsistencies of groups of associations between database and query items, e.g. to inhibit matchings of multiple query descriptors to the same database descriptor if the query descriptors are mutually different. This is only one example of additional structural knowledge. Please refer to the publications below for more details.
The basic place recognition pipeline (above the horizontal dashed
line) can be extended with additional information (below this line). Established
approaches are standardization of descriptors and sequence processing. We work on algorithms that exploit additional knowledge, for example the intra-set similarities of database or query images.
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