Title : 
Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor
         
        
            Author : 
Goto, Kunihiro ; Kidono, Kiyosumi ; Kimura, Yoshikatsu ; Naito, Takashi
         
        
            Author_Institution : 
Toyota Central R&D Labs., Inc., Nagakute, Japan
         
        
        
        
        
        
            Abstract : 
This paper proposes a pedestrian detection and direction estimation method by the cascade approach with multiclassifiers using the Feature Interaction Descriptor (FIND). FIND describes the high-level properties of an object´s appearance by computing pair-wise interactions of adjacent regionlevel features. To perform efficient and accurate detection using FIND, we employ the cascade approach with multiclassifiers specialized in both the direction of a pedestrian and the distance of the pedestrian from a camera. Using this framework, the developed system can improve the detection performance and provide information of the direction of a pedestrian simultaneously. The experimental results show that superior detection performance and direction estimation results were obtained by our method.
         
        
            Keywords : 
driver information systems; image classification; image sensors; object detection; camera; cascade detector; direction estimation; feature interaction descriptor; multiclassifiers; pairwise adjacent region level feature interactions; pedestrian detection; Cameras; Computational efficiency; Detectors; Estimation; Feature extraction; Histograms; Training;
         
        
        
        
            Conference_Titel : 
Intelligent Vehicles Symposium (IV), 2011 IEEE
         
        
            Conference_Location : 
Baden-Baden
         
        
        
            Print_ISBN : 
978-1-4577-0890-9
         
        
        
            DOI : 
10.1109/IVS.2011.5940432