Barış, İpekBaştanlar, Yalın2019-02-052019-02-052018Barış, İ., and Baştanlar, Y. (2018, October 16-19). Classification and tracking of traffic scene objects with hybrid camera systems. Paper presented at the 20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017. doi:10.1109/ITSC.2017.8317588978-153861525-6https://doi.org/10.1109/ITSC.2017.8317588https://hdl.handle.net/11147/709120th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017; Mielparque YokohamaYokohama, Kanagawa; Japan; 16 October 2017 through 19 October 2017In a hybrid camera system combining an omnidirectional and a Pan-Tilt-Zoom (PTZ) camera, the omnidirectional camera provides 360 degree horizontal field-of-view, whereas the PTZ camera provides high resolution at a certain direction. This results in a wide field-of-view and high resolution camera system. In this paper, we exploit this hybrid system for real-time object classification and tracking for traffic scenes. The omnidirectional camera detects the moving objects and performs an initial classification using shape-based features. Concurrently, the PTZ camera classifies the objects using high resolution frames and Histogram of Oriented Gradients (HOG) features. PTZ camera also performs high-resolution tracking for the objects classified as the target class by the omnidirectional camera. The object types we worked on are pedestrian, motorcycle, car and van. Extensive experiments were conducted to compare the classification accuracy of the hybrid system with single camera alternatives.eninfo:eu-repo/semantics/openAccessHybrid camera systemObject detectionOmnidirectional cameraVehicle detectionConference Object2-s2.0-8504628860310.1109/ITSC.2017.8317588