PROMETHEUS database: A multimodal corpus for research on modeling and interpreting human behavior

Ntalampiras, Stavros; Arsic, D.; Stormer, A; Ganchev, Todor; Potamitis, Ilyas; Fakotakis, Nikos

doi:10.1109/icdsp.2009.5201142

Cited by 13 publications

(10 citation statements)

References 6 publications

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“…The multimodal multisensory PROMETHEUS database [16] was created in support of RTD activities aiming at the creation of a framework for monitoring and interpretation of human behaviours in unrestricted indoor and outdoor environments. The database consists of approximately four hours of recordings, representative for two application scenarios: smart-home and public security (airport and ATM -bankomat, surveillance).…”

Section: Prometheus Databasementioning

confidence: 99%

Fusion of acoustic and optical sensor data for automatic fight detection in urban environments

Andersson

Ntalampiras

Ganchev

et al. 2010

2010 13th International Conference on Information Fusion

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We propose a two-stage method for detection of abnormal behaviours, such as aggression and fights in urban environment, which is applicable to operator support in surveillance applications. The proposed method is based on fusion of evidence from audio and optical sensors. In the first stage, a number of modalityspecific detectors perform recognition of low-level events. Their outputs act as input to the second stage, which performs fusion and disambiguation of the firststage detections. Experimental evaluation on scenes from the outdoor part of the PROMETHEUS database demonstrated the practical viability of the proposed approach. We report a fight detection rate of 81% when both audio and optical information are used. Reduced performance is observed when evidence from audio data is excluded from the fusion process. Finally, in the case when only evidence from one camera is used for detecting the fights, the recognition performance is poor.

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Section: Prometheus Databasementioning

confidence: 99%

Fusion of acoustic and optical sensor data for automatic fight detection in urban environments

Andersson

Ntalampiras

Ganchev

et al. 2010

2010 13th International Conference on Information Fusion

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“…The data used in this paper has been recorded during the 7th Framework EU Project PROMETHEUS (Ntalampiras et al, 2009). We use data from two smart home indoor scenarios.…”

Section: Database and Setupmentioning

confidence: 99%

“…Section 4 presents our extension to the Viterbi Tracking algorithm for event detection. Experiment on the PROMETHEUS dataset (Ntalampiras et al, 2009) are shown in Section 5 and we conclude in Section 6.…”

Section: Introductionmentioning

confidence: 99%

Event Detection in a Smart Home Environment Using Viterbi Filtering and Graph Cuts in a 3d Voxel Occupancy Grid

Hofmann¹,

Kaiser²,

Lehment³

et al. 2011

Proceedings of the International Conference on Computer Vision Theory and Applications

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In this paper we present a system for detecting unusual events in smart home environments. A primary application of this is to prolong independent living for elderly people at their homes. We show how to effectively combine information from multiple heterogeneous sensors which are typically present in a smart home scenario. Data fusion is done in a 3D voxel occupancy grid. Graph Cuts are used to accurately reconstruct people in the scene. Additionally we present a joint multi object Viterbi tracking framework, which allows tracking of all people, and simultaneously detecting critical events such as fallen persons.

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“…Observing this we are able to detect scenarios with feeding expert knowledge into the network structure. The performance of this approach will be demonstrated on the PROMETHEUS data set [17], which has been created for the comparison of tracking and behavior detection systems, and introduced new sensors such as thermal infrared, 3D cameras and also used audio. Ground truth is provided both for the person locations and associated events.…”

Section: Introductionmentioning

confidence: 99%

Applying Bayes Markov chains for the detection of ATM related scenarios

Arsic

Lyutskanov

Kaiser

et al. 2009

2009 Workshop on Applications of Computer Vision (WACV)

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Video surveillance systems have been introduced in various fields of our daily life to enhance security and protect individuals and sensitive infrastructure. Up to now it has been usually utilized as a forensic tool for after the fact investigations and are commonly monitored by human operators. In order to assist these and to be able to react in time, a fully automated system is desired. In this work we will present a multi camera surveillance system, which is required to resolve heavy occlusions, to detect robberies at ATM machines. The resulting trajectories will be analyzed for so called Low Level Activities (LLA), such as walking, running and stationarity, applying simple but robust approaches. The results of the LLA analysis will subsequently be fed into a Bayesian Network, that is used as a stochastic model to model so called High Level Activities (HLA). Introducing state transitions between HLAs will allow a temporal modeling of a complex scene. This can be represented by a Markovian process.

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PROMETHEUS database: A multimodal corpus for research on modeling and interpreting human behavior

Cited by 13 publications

References 6 publications

Fusion of acoustic and optical sensor data for automatic fight detection in urban environments

Fusion of acoustic and optical sensor data for automatic fight detection in urban environments

Event Detection in a Smart Home Environment Using Viterbi Filtering and Graph Cuts in a 3d Voxel Occupancy Grid

Applying Bayes Markov chains for the detection of ATM related scenarios

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