Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Pattern Analysis and Machine Intelligence Year : 2016

Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition

(1, 2) , (3) , (4) , (4) , (4) , (3) , (4) , (1, 2)
1
2
3
4

Abstract

Combining multimodal concept streams from heterogeneous sensors is a problem superficially explored for activity recognition. Most studies explore simple sensors in nearly perfect conditions, where temporal synchronization is guaranteed. Sophisticated fusion schemes adopt problem-specific graphical representations of events that are generally deeply linked with their training data and focused on a single sensor. This paper proposes a hybrid framework between knowledge-driven and probabilistic-driven methods for event representation and recognition. It separates semantic modeling from raw sensor data by using an intermediate semantic representation, namely concepts. It introduces an algorithm for sensor alignment that uses concept similarity as a surrogate for the inaccurate temporal information of real life scenarios. Finally, it proposes the combined use of an ontology language, to overcome the rigidity of previous approaches at model definition, and a probabilistic interpretation for ontological models, which equips the framework with a mechanism to handle noisy and ambiguous concept observations, an ability that most knowledge-driven methods lack. We evaluate our contributions in multimodal recordings of elderly people carrying out IADLs. Results demonstrated that the proposed framework outperforms baseline methods both in event recognition performance and in delimiting the temporal boundaries of event instances.
Fichier principal
Vignette du fichier
crispim_etal_pami_spec_issu_v7.2 (1).pdf (4.21 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01399025 , version 1 (18-11-2016)

Identifiers

Cite

Carlos F Crispim-Junior, Vincent Buso, Konstantinos Avgerinakis, Georgios Meditskos, Alexia Briassouli, et al.. Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016, 38, pp.1598 - 1611. ⟨10.1109/TPAMI.2016.2537323⟩. ⟨hal-01399025⟩
181 View
463 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More