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Sensors 2012, 12(9), 12126-12152; doi:10.3390/s120912126
Article

Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI

* , , ,  and
Received: 2 May 2012; in revised form: 31 July 2012 / Accepted: 21 August 2012 / Published: 5 September 2012
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Abstract: Recent advances in technologies for capturing video data have opened a vast amount of new application areas in visual sensor networks. Among them, the incorporation of light wave cameras on Ambient Intelligence (AmI) environments provides more accurate tracking capabilities for activity recognition. Although the performance of tracking algorithms has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This paper advocates for the introduction of a part-based representational level in cognitive-based systems in order to accurately represent the novel sensors’ knowledge. The paper also reviews the theoretical and practical issues in part-whole relationships proposing a specific taxonomy for computer vision approaches. General part-based patterns for human body and transitive part-based representation and inference are incorporated to an ontology-based previous framework to enhance scene interpretation in the area of video-based AmI. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP) application for the elaboration of live market researches.
Keywords: visual sensor networks; light wave; structured light; time-of-flight; cognitive vision; ontology-based; ambient intelligence; social signal processing visual sensor networks; light wave; structured light; time-of-flight; cognitive vision; ontology-based; ambient intelligence; social signal processing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Serrano, M.Á.; Gómez-Romero, J.; Patricio, M.Á.; García, J.; Molina, J.M. Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI. Sensors 2012, 12, 12126-12152.

AMA Style

Serrano MÁ, Gómez-Romero J, Patricio MÁ, García J, Molina JM. Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI. Sensors. 2012; 12(9):12126-12152.

Chicago/Turabian Style

Serrano, Miguel Ángel; Gómez-Romero, Juan; Patricio, Miguel Ángel; García, Jesús; Molina, José Manuel. 2012. "Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI." Sensors 12, no. 9: 12126-12152.


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