稀疏光流快速计算的动态目标检测与跟踪

动态目标的检测与跟踪作为图像处理和计算机视觉学科的重要分支，广泛应用于军事和民用等各个领域。文中提出一种基于稀疏光流快速计算的目标检测和跟踪新方法，该方法通过计算能反映图像特征的特定像素点光流矢量来实现目标检测和跟踪，同时结合图像金字塔技术，可以检测和跟踪运动速度更快、运动尺度更大的目标。文中将该方法分别与稠密光流方法和基于颜色特征方法作对比，结果表明该方法有计算量小、能很好应对目标遮挡情况和能检测和跟踪运动速度较快的目标等诸多优点。实验在多种条件下对该方法进行了验证，跟踪准确率都能达到80%以上，且基本能符合实时性的要求，说明该方法具有可行性和实用价值。

Dynamic target detection and tracking based on fast computation using sparse optical flow

As an important branch of image processing and computer vision, dynamic target detection and tracking is widely applied in military, civilian and other fields. A new method of target detection and tracking based on fast computation using sparse optical flow is proposed in this paper. Only optical flow vectors of specific pixels which can reflect features of the image are calculated in this method, and image pyramid is combined to detect and track faster and larger-scale motion. In this paper, the new method is compared with methods based on dense optical flow and color feature respectively. The comparison results show that the method proposed in this paper has many advantages, such as high calculation efficiency, well dealing with target occlusion, well detecting and tracking fast target and so on. Experiments under various conditions are done to validate the effect of this method. Tracking accuracy can reach more than 80% in most cases and the method can also meet the real-time requirement. This indicates that the method is feasible and practical.