Innovative analysis methods applied to data extracted by off-the-shelf peripherals can provide useful results in activity recognition without requiring large computational resources. In this paper a framework is proposed for automated posture and gesture recognition, exploiting depth data provided by a commercial tracking device. The detection problem is handled as a semantic-based resource discovery. A general data model and the corresponding ontology provide the formal underpinning for posture and gesture annotation via standard Semantic Web languages. Hence, a logic-based matchmaking, exploiting non-standard inference services, allows to: (i) detect postures via on-the-fly comparison of the annotations with standard posture descriptions stored as instances of a proper Knowledge Base; (ii) compare subsequent postures in order to recognize gestures. The framework has been implemented in a prototypical tool and experimental tests have been carried out on a reference dataset. Preliminary results indicate the feasibility of the proposed approach.

Semantic Matchmaking for Kinect-Based Posture and Gesture Recognition / Ruta, Michele; Scioscia, Floriano; di Summa, Maria; Ieva, Saverio; DI SCIASCIO, Eugenio; Sacco, Marco. - In: INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING. - ISSN 1793-7108. - 8:4(2014), pp. 491-514. [10.1142/S1793351X14400169]

Semantic Matchmaking for Kinect-Based Posture and Gesture Recognition

RUTA, Michele;SCIOSCIA, Floriano;IEVA, Saverio;DI SCIASCIO, Eugenio;
2014-01-01

Abstract

Innovative analysis methods applied to data extracted by off-the-shelf peripherals can provide useful results in activity recognition without requiring large computational resources. In this paper a framework is proposed for automated posture and gesture recognition, exploiting depth data provided by a commercial tracking device. The detection problem is handled as a semantic-based resource discovery. A general data model and the corresponding ontology provide the formal underpinning for posture and gesture annotation via standard Semantic Web languages. Hence, a logic-based matchmaking, exploiting non-standard inference services, allows to: (i) detect postures via on-the-fly comparison of the annotations with standard posture descriptions stored as instances of a proper Knowledge Base; (ii) compare subsequent postures in order to recognize gestures. The framework has been implemented in a prototypical tool and experimental tests have been carried out on a reference dataset. Preliminary results indicate the feasibility of the proposed approach.
2014
Semantic Matchmaking for Kinect-Based Posture and Gesture Recognition / Ruta, Michele; Scioscia, Floriano; di Summa, Maria; Ieva, Saverio; DI SCIASCIO, Eugenio; Sacco, Marco. - In: INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING. - ISSN 1793-7108. - 8:4(2014), pp. 491-514. [10.1142/S1793351X14400169]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/90201
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