Development of the methods for tracking and behavior understanding of vehicles and pedestrians in urban traffic scenes

城市交通场景中车辆和行人的跟踪和行为理解方法的开发

基本信息

批准号：
14580407
负责人：
KAMIJO Shunsuke
金额：
$ 2.05万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2002
资助国家：
日本
起止时间：
2002 至 2003
项目状态：
已结题

项目摘要

Last fiscal year, we developed an algorithm which is able to track both rigid objects such as vehicles and flexible objects such as pedestrians in images.This fiscal year, improving this tracking algorithm, we enabled to get detail trajectory of these various types of moving objects, and implemented a prototype of Real-time System.On the other hand, we developed a system which detects events based on experiments mainly conducted on Metropolitan Expressway.By applying the Spatio-Temporal trajectory of each object from the algorithm, this system classifies traffic events by using a rule-based reasoning method.First Coordinate-class operator extracts Spatio-Temporal trajectory of each vehicle from tracking results.Secondly, Behavior-class operator extracts behavior of each vehicle such as "Stall" and "Stop" from the Spatio-Temporal trajectories.Lastly, using behaviors information of vehicles on the image, Event-class operator detects traffic events such as accidents, congestion, etc.As above, our event detection, system utilizes a semantic hierarchy consisting of three kinds of operators (Coordinate-class, Behavior-class and Event-class) and has high affinity with the human cognitive process.So, it can be said that development of algorithm which tracks vehicles and pedestrians simultaneously achieved some positive success. When it came to the event detection, fundamental algorithm was developed to recognize behaviors of vehicles in particular. We consider that this algorithm can also be applied to images including vehicles and pedestrians, and will continue the verification of the system extensibility.

上一个财政年度，我们开发了一种算法，能够跟踪诸如车辆和柔性物体（例如行人在图像中的行人）之类的刚性物体。这个财政年度，改善了这种跟踪算法，我们使我们能够获得这些各种类型的移动物体，并在其他系统上实施了实现的实验，从而实现了这些群体，从而实现了实验，从而实现了实现的实验，该事件是实现的，该事件是在实验中实现的，该元素是实现的，该事件是实现的，该系统是实现的。通过使用基于规则的推理方法，通过应用算法中每个物体的每个对象的时空轨迹进行分类。车辆在图像上的行为信息，事件级操作员检测到交通事件，例如事故，托运等。如上所述，我们的事件检测，系统采用语义层次结构，包括三种类型的操作员（坐标，行为级，行为级和事件级）组成的语义层次结构（坐标，行为级和事件级），并具有与人类认知过程的高亲和力。成功。当涉及事件检测时，开发了基本算法，以特别识别车辆的行为。我们认为该算法也可以应用于包括车辆和行人在内的图像，并将继续验证系统的可扩展性。