中国图象图形学报A
中國圖象圖形學報A
중국도상도형학보A
JOURNAL OF IMAGE AND GRAPHICS
2010年
2期
301-306
,共6页
智能交通%车辆检测%车辆跟踪%夜间%高速公路
智能交通%車輛檢測%車輛跟蹤%夜間%高速公路
지능교통%차량검측%차량근종%야간%고속공로
intelligent traffic%vehicle detection%vehicle tracking%nighttime%highway
针对高速公路夜间行驶车辆的特点,基于最优化理论提出了一种鲁棒的车辆检测和跟踪算法,对现有的车灯提取算法和轨迹跟踪规则进行了改进,不仅可自动统计和显示车流量,车速等交通信息,并且能对逆行、拥堵、自由流停车等交通车辆事件做出自动判断.实验结果表明,该算法复杂性低,实时性好,在夜间路况较好的条件下车辆检测成功率达95%以上,在拥挤交通条件下,检测正确率在80%左右.
針對高速公路夜間行駛車輛的特點,基于最優化理論提齣瞭一種魯棒的車輛檢測和跟蹤算法,對現有的車燈提取算法和軌跡跟蹤規則進行瞭改進,不僅可自動統計和顯示車流量,車速等交通信息,併且能對逆行、擁堵、自由流停車等交通車輛事件做齣自動判斷.實驗結果錶明,該算法複雜性低,實時性好,在夜間路況較好的條件下車輛檢測成功率達95%以上,在擁擠交通條件下,檢測正確率在80%左右.
침대고속공로야간행사차량적특점,기우최우화이론제출료일충로봉적차량검측화근종산법,대현유적차등제취산법화궤적근종규칙진행료개진,불부가자동통계화현시차류량,차속등교통신식,병차능대역행、옹도、자유류정차등교통차량사건주출자동판단.실험결과표명,해산법복잡성저,실시성호,재야간로황교호적조건하차량검측성공솔체95%이상,재옹제교통조건하,검측정학솔재80%좌우.
In the video detection system of highway traffic flow, it is difficult to detect vehicles. This paper studies nighttime highway traffic vehicles and proposes a robust vehicle detection and tracking algorithm based on optimization theory. The proposed algorithm improves the previous methods for headlight detection and the rules for trajectory tracking. At the same time, it can not only automatically present traffic flow and vehicles speed statistically, but also recognize traffic vehicle event such as jam-packed or driving against the traffic. Experiment results demonstrate the algorithm has lower complexity and better performance than other methods. The detection rate can reach up to 95% or so, robust with low complexity, real-time feature and its detection ratio reaches up to 95% in smooth traffic conditions and 80% in traffic jams.
