A Vehicle Detection and Tracking Algorithm Using Local Features of The Vehicle in Tunnel
차량의 부분 특징을 이용한 터널 내에서의 차량 검출 및 추적 알고리즘

Hyun-Tae Kim, Gyu-Young Kim, Jin-Kyu Do, Jang Sik Park
2013 The Journal of the Korea institute of electronic communication sciences  
In this paper, an efficient vehicle detection and tracking algorithm for detection incident in tunnel is proposed. The proposed algorithm consists of three steps. The first one is a step for background estimates, low computational complexity and memory consumption Running Gaussian Average (RGA) is used. The second step is vehicle detection step, Adaboost algorithm is applied to this step. In order to reduce false detection from a relatively remote location of the vehicles, local features
more » ... ng to height of vehicles are used to detect vehicles. If the local features of an object are more than the threshold value, the object is classified as a vehicle. The last step is a vehicle tracking step, the Kalman filter is applied to track moving objects. Through computer simulations, the proposed algorithm was found that useful to detect and track vehicles in the tunnel. 키워드 Adaboost Algorithm, Local Feature, Kalman Filter, Vehicle Detection
doi:10.13067/jkiecs.2013.8.8.1179 fatcat:yeeddn2owfcuxifnaj34v6jsqe