Maritime Objects Recognition And Tracking Based On Video

Video moving targets detection,recognition and tracking are one of the most important issues in the field of computer vision. It has wide application prospects in many areas, such as video surveillance,human-computer interaction,robot visual navigation and intelligent traffic control. Implement of maritime objects detection,recognition and tracking is significant for statistics of vessel information,avoiding sea collision between vessels and coastal defense.This paper mainly researches maritime ship identification and tracking technology. First, it describes current development status of maritime moving target detection and tracking research, and then outlines some main methods of salient region extraction, moving target identification and tracking, and we present a method of ship detection based on the visual attention and HOG feature. Finally we use the particle filter of multi-feature combining method to track the moving targets. The main research innovations and contributions are summarized as follows:1. We take a deep research into the model of visual attention, and propose a method of salient ship region detection based on improved visual attention. Threshold division and region extraction are used to get salient ship region quickly based on saliency map to lay the foundation for ship identification.2. Based on the attention model and HOG feature, we present a ship target detection mechanism of visual attention and HOG feature two-way integration, and simulate the process of interactive visual about the human visual awareness in the "active search" and unconscious "passive attracted by". We quickly get salient ship region through the visual attention, reduce the search region, and then achieve the precise recognition in the saliency ship region through the HOG feature and Learning mechanism. Simultaneously, we propose a method to get candidate ship location quickly by edge detection and region extraction. Experiment results show that this two-way integration mechanism of ship target detection has feature of high accuracy, fast processing speed, and it basically meet the requirements of real-time processing for complex scene.3. We explore the particle filtering method and put it into the ship tracking system. We improve the accuracy and robustness of the tracking system through the combination of HSV color histogram with shape features. The system also shows a good performance in many situations such as multi-target tracking, target under cross-blocked, and so on.