Comparing Visual Data Fusion Techniques Using FIR and Visible Light Sensors to Improve Pedestrian Detection

Comparing Visual Data Fusion Techniques Using FIR and Visible Light Sensors to Improve Pedestrian Detection

Pedestrian detection is an important field in computer vision with applications in surveillance, robotics and driver assistance systems. The quality of such systems can be improved by the simultaneous use of different sensors. This paper proposes three different fusion techniques to combine the adva...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Thomanek, J., Ritter, M., Lietz, H., Wanielik, G.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Cameras
Classification
Data Fusion
Feature extraction
Finite impulse response filter
Image Processing
Image sensors
Pedestrian Detection
Sensor fusion
Vectors
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Beschreibung
Zusammenfassung:Pedestrian detection is an important field in computer vision with applications in surveillance, robotics and driver assistance systems. The quality of such systems can be improved by the simultaneous use of different sensors. This paper proposes three different fusion techniques to combine the advantages of two vision sensors -- a far-infrared (FIR) and a visible light camera. Different fusion methods taken from various levels of information representation are briefly described and finally compared regarding the results of the pedestrian classification.
DOI:10.1109/DICTA.2011.27