抗噪Snake模型及其在行人轮廓提取中的应用  

Anti-noise Snake Model and Application in Pedestrian Contour Extraction

作　　者：刘述民[1,2] 徐栩娟 黄影平[2] 

机构地区：[1]江西理工大学软件学院,江西南昌330013 [2]上海理工大学光电信息与计算机工程学院,上海200093 [3]江西省民政学校,江西南昌330013

出　　处：《信息与控制》2015年第5期564-569,576,共7页Information and Control

基　　金：江西理工大学校级科研基金资助项目(NSFJ2015-G34);国家自然科学基金资助项目(61374197)

摘　　要：将Snake模型和立体分割技术相结合提出了从交通视图中分割出潜在行人目标,并提取其轮廓曲线的方法,针对Snake模型易受噪声干扰的缺陷,将梯度向量流(GVF)模型和基于轮廓曲线的角点检测技术相结合,提出抗噪Snake模型.此外,为了克服GVF模型的初始轮廓曲线设置困难及GVF场迭代过程的计算复杂等缺陷,还提出了初始轮廓曲线的优化及相适应GVF场的建立方法,最后,选择了4个不同交通场景中的行人为研究对象,测试和对比GVF模型和抗噪Snake模型在行人轮廓提取中的应用效果,验证了抗噪Snake模型在复杂环境中行人轮廓提取的有效性.We present a novel approach that combines the snake model with a 3D segmentation technique to segment potential pedestrians from traffic images and extract their contour curves. The snake model is highly prone to interference by noise, and thus, an anti-noise snake model is proposed that combines the gradient vector flow （GVF） model with a tailored corner detection approach. In addition, an optimization method for the initial contour curve and a modeling method for the adaptive GVF field are proposed to overcome problems associated with establishing the initial contour curve, given the high computational complexity of the GVF model during an iteration process and other considerations. This optimization method reduces the time required to effectively extract contour curves. Finally, using pedestrians in complex traffic scenarios as objects, the performances of the GVF model and anti-noise snake model are tested and compared for extracting pedestrian contours. Results show that the anti-noise snake model is effective for extracting pedestrian contour curves in complex traffic scenarios.

关 键 词：抗噪Snake模型 轮廓提取 角点检测 梯度向量流(GVF)模型 立体分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]