VBAI2013新功能-跟踪目标

石鑫华视觉

跟踪目标

NI Vision 2013中新增了跟踪目标功能。这个功能一般可以用于安防与监控、交通流量管控、医学、工业、机器人和导航、人机交互、目标建模（三维）、生物力学（仿生学）等领域。与匹配有些类似，也是寻找目标，但是可以返回上下两幅图像目标之间的位移。
Object Tracking

The NI Vision Development Module 2013 introduces a new algorithm for object tracking, which tracks the location of an object over a sequence of images to determine how it is moving relative to other objects in the image. Object tracking has many uses in application areas such as:

• Security and surveillance - In the surveillance industry, objects of interest such as people and vehicles can be tracked. Object tracking can be used for detecting trespassing or observing anomalies like unattended baggage.
• Traffic management - The flow of traffic can be analyzed, and collisions detected.
  

• Medicine - Cells can be tracked in medical images.
• Industry - Defective items can be detected and tracked.
• Robotics and navigation - Robots can follow the trajectory of an object. Robotic assistance can maneuver in a factory (de-palletizing objects).
• Human-computer interaction (HCI) - Users can be tracked in a gaming environment.
• Object modeling - An object tracked from multiple perspectives can be used to create a partial 3D model of the object.
• Bio-mechanics - Tracking body parts to interpret gestures or movements.
  

                               
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Figure 3: Example of object tracking for a traffic monitoring application

NI Vision implements two object tracking algorithms: Mean shift and EM-based mean shift. Mean shift tracks the user-defined objects by iteratively updating the location of the object while EM-based mean shift not only tracks the location but also the shape and scale of the object is adapted for each frame. Both algorithms are tolerant of gradual changes in the tracked object, including geometric transformations such as shifting, rotation, scaling, or partial occlusion of the object.