A visual place recognition procedure with a Markov chain based filter

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Filipe Neves Santos (Author) FEUP; Paulo Gomes da Costa (Author) FEUP; António Paulo Moreira (Author) FEUP

Conference proceedings International

Title: 2014 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2014

Pages: 333-338

IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Espinho, PORTUGAL, MAY 14-15, 2014

Indexing

ISI Web of Knowledge - 8 Citations

Scopus - 6 Citations

Other information

Authenticus ID: P-009-Q33

DOI: 10.1109/icarsc.2014.6849808

Abstract (EN): Recognizing a place with a visual glance is the first capacity used by humans to understand where they are. Making this capacity available to robots will make it possible to increase the redundancy of the localization systems available in the robots, and improve semantic localization systems. However, to achieve this capacity it is necessary to build a robust visual place recognition procedure that could be used by an indoor robot. This paper presents an approach that from a single image estimates the robot location in the semantic space. This approach extracts from each camera image a global descriptor, which is the input of a Support Vector Machine classifier. In order to improve the classifier accuracy a Markov chain formalism was considered to constraint the probability flow according the place connections. This approach was tested using videos acquired from three robots in three different indoor scenarios - with and without the Markov chain filter. The use of Markov chain filter has shown a significantly improvement of the approach accuracy.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6