A multi-modal video analysis approach for car park fire detection

In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by visual flame feature analysis and amplitude disorder detection. In order to detect the low-cost flame related features, moving objects in visual images are analyzed over time. If an object possesses high probability for each of the flame characteristics, it is labeled as candidate flame region. Simultaneously, the amplitude disorder is also investigated. Also labeled as candidate flame regions are regions with high accumulative amplitude differences and high values in all detail images of the amplitude image's discrete wavelet transform. Finally, when there is overlap of at least one of the visual and amplitude candidate flame regions, fire alarm is raised. The smoke detector, on the other hand, focuses on global changes in the depth images of the time-of-flight camera, which do not have significant impact on the amplitude images. It was found that this behavior is unique for smoke. Experiments show that the proposed detectors improve the accuracy of fire detection in car parks. The flame detector has an average flame detection rate of 93%, with hardly any false positive detection, and the smoke detection rate of the TOF based smoke detector is 88%. © 2012 Elsevier Ltd

Multi-modal video analysis for early fire detection

In dit proefschrift worden verschillende aspecten van een intelligent videogebaseerd branddetectiesysteem onderzocht. In een eerste luik ligt de nadruk op de multimodale verwerking van visuele, infrarood en time-of-flight videobeelden, die de louter visuele detectie verbetert. Om de verwerkingskost zo minimaal mogelijk te houden, met het oog op real-time detectie, is er voor elk van het type sensoren een set ’low-cost’ brandkarakteristieken geselecteerd die vuur en vlammen uniek beschrijven. Door het samenvoegen van de verschillende typen informatie kunnen het aantal gemiste detecties en valse alarmen worden gereduceerd, wat resulteert in een significante verbetering van videogebaseerde branddetectie. Om de multimodale detectieresultaten te kunnen combineren, dienen de multimodale beelden wel geregistreerd (~gealigneerd) te zijn. Het tweede luik van dit proefschrift focust zich hoofdzakelijk op dit samenvoegen van multimodale data en behandelt een nieuwe silhouet gebaseerde registratiemethode. In het derde en tevens laatste luik van dit proefschrift worden methodes voorgesteld om videogebaseerde brandanalyse, en in een latere fase ook brandmodellering, uit te voeren. Elk van de voorgestelde technieken voor multimodale detectie en multi-view lokalisatie zijn uitvoerig getest in de praktijk. Zo werden onder andere succesvolle testen uitgevoerd voor de vroegtijdige detectie van wagenbranden in ondergrondse parkeergarages

Pedestrian detection by range imaging

Remote detection by camera offers a versatile means for recording people activities. Relying principally on changes in video images, the method tends to fail in presence of shadows and illumination changes. This paper explores a possible remedy to these problems by using range cameras instead of conventional video cameras. As range is an intrinsic measure of object geometry, it is basically not affected by illumination. The study described in this paper considers range detection by two state-of-the art cameras, namely a stereo and a time-of-flight camera. Performed investigations consider typical situations of pedestrian detection. The presented results are analyzed and compared in performance with conventional results. The study shows the effective potential of range camera to get rid of light change problems like shadow effects but also presents some current limitations of range cameras

PEDESTRIAN DETECTION BY RANGE IMAGING

changing illumination Remote detection by camera offers a versatile means for recording people activities. Relying principally on changes in video images, the method tends to fail in presence of shadows and illumination changes. This paper explores a possible remedy to these problems by using range cameras instead of conventional video cameras. As range is an intrinsic measure of object geometry, it is basically not affected by illumination. The study described in this paper considers range detection by two state-of-the art cameras, namely a stereo and a time-of-flight camera. Performed investigations consider typical situations of pedestrian detection. The presented results are analyzed and compared in performance with conventional results. The study shows the effective potential of range camera to get rid of light change problems like shadow effects but also presents some current limitations of range cameras.