Vehicle surveillance system provides a large range of informational services for the driver and administrator such as multiview road and driver surveillance videos from multiple cameras mounted on the vehicle, video shots monitoring driving behavior and highlighting the traffic conditions on the roads. How to retrieval driver’s specific behavior, such as ignoring pedestrian, operating infotainment, near collision or running the red light, is difficult in large scale driving data. Annotation and retrieving of these video streams has an important role on visual aids for safety and driving behavior assessment. In a vehicle surveillance system, video as a primary data source requires effective ways of retrieving the desired clip data from a database. And data from naturalistic studies allow for an unparalleled breadth and depth of driver behavior analysis that goes beyond the quantification and description of driver distraction into a deeper understanding of how drivers interact with their vehicles. To do so, a model that classifies vehicle video data on the basis of traffic information and its semantic properties which were described by driver’s eye gaze orientation was developed in this paper. The vehicle data from OBD and sensors is also used to annotate the video. Then the annotated video data based on the model is organized and streamed by retrieval platform and adaptive streaming method. The experimental results show that this model is a good example for evidence-based traffic instruction programs and driving behavior assessment.

Streaming media applications is currently limited by high bandwidth requirements. It is a challenging problem to provide the required quality of service (QoS) for the efficient transmission of video data under the varying network conditions such as the time-varying packet loss and fluctuating bandwidth. On Internet the most important part for streaming media transmission application is QoS control mechanism which including two kinds of QoS control method, based on end to end and network. A wireless streaming media forward platform based on the mixed quality-of-service (QoS) control system is introduced in this paper. The theoretical knowledge related to the quality of service and mixed quality of service control of the feasibility and characteristics are analyzed, and introduced a comprehensive quality of service in theory. This system combines network control and end to end quality of service control. The network of the system is optimized to support quality of service, using the underlying network devices, network bandwidth optimization, network structure adapted to meet the both ends of the quality of service. At both ends, from the delay, jitter, etc. are adjusted, by the addition of the timestamp and other information on the dynamic adjustment of the speed of data transmission. Through improving the control of two ends QoS and media streaming forward server, the video streaming from ships on the sea is transferred to the Internet by microwave and then linked to common Internet and mobile phone users through carrier networks(wired and wireless), which realized the real time supervision.