In this paper, a novel particle filter–based visual contour tracking method is proposed, which uses inner-contour model to track contour object under complex background. The purpose is to achieve effectiveness and robustness against complex background. To that end, the proposed method first utilized Sobel edge detector to detect the edge information along the normal line of the contour. Then, it sampled the inner part of the normal line to get the local color information, which was then combined with the edge information to construct new normal line likelihood. After that, all the inner color information was used to construct global color likelihood. Finally, the edge information, local color information, and global color information were fused into new observation likelihood. Experimental results showed that the proposed method was robust for contours tracking under complex background, and it was also computationally efficient and can run in real-time completely.

中文翻译：

---

复杂背景下基于内轮廓模型粒子滤波的视觉轮廓跟踪

本文提出了一种新颖的基于粒子滤波的视觉轮廓跟踪方法，该方法利用内轮廓模型在复杂背景下跟踪轮廓物体。目的是在复杂背景下实现有效性和鲁棒性。为此，所提出的方法首先利用Sobel边缘检测器来检测沿轮廓法线的边缘信息。然后，它对法线的内部进行采样以获得局部颜色信息，然后将其与边缘信息结合以构造新的法线可能性。之后，所有内部颜色信息都用于构造全局颜色可能性。最后，将边缘信息，局部颜色信息和全局颜色信息融合到新的观察可能性中。