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Autonomous Robots
Erschienen in: Autonomous Robots 4/2012

01.05.2012

PLISS: labeling places using online changepoint detection

verfasst von: Ananth Ranganathan

Erschienen in: Autonomous Robots | Ausgabe 4/2012

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Abstract

A shared vocabulary between humans and robots for describing spatial concepts is essential for effective human robot interaction. Towards this goal, we present a novel technique for place categorization from visual cues called PLISS (Place Labeling through Image Sequence Segmentation). PLISS is different from existing place categorization systems in two major ways—it inherently works on video and image streams rather than single images, and it can detect “unknown” place labels, i.e. place categories that it does not know about. PLISS uses changepoint detection to temporally segment image sequences which are subsequently labeled. Changepoint detection and labeling are performed inside a systematic probabilistic framework. Unknown place labels are detected by using a probabilistic classifier and keeping track of its label uncertainty. We present experiments and comparisons on the large and extensive VPC dataset. We also demonstrate results using models learned from images downloaded from Google’s image search.
Nächster Artikel Analysis of autonomous cooperative assembly using coordination schemes by heterogeneous robots using a control basis approach

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Metadaten
Titel
PLISS: labeling places using online changepoint detection
verfasst von
Ananth Ranganathan
Publikationsdatum
01.05.2012
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 4/2012
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-012-9273-4

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