整体视觉结构模型及其在道路环境感知中的应用

发布时间：2018-07-01 16:48

本文选题：目标检测 + 环境感知　；参考：《计算机工程》2016年10期

【摘要】：智能车辆道路环境感知中道路目标的准确快速检测,是智能车辆安全辅助驾驶和自动驾驶中的难点。为此,在整体视觉结构模型的基础上,模拟人体由局部到整体的认知机理,并基于原目标局部模型引入结构化信息及概率统计模型,得到更具姿态和尺度适应性的整体视觉结构模型。该模型在弱标注训练样本的基础上可实现目标局部特征区域的自动标注功能,从而获得更具特征描述性的目标特征。实验结果表明,该模型可实现道路典型目标的高检测率和低误码率,且算法效率与经典算法相比有所提高。
[Abstract]:Accurate and fast detection of road target in intelligent vehicle road environment perception is a difficult point in intelligent vehicle safety assistant driving and automatic driving. Therefore, based on the global visual structure model, the cognitive mechanism of human body from local to global is simulated, and the structured information and probabilistic statistical model are introduced based on the local model of the original target. A global visual structure model with more adaptability to attitude and scale is obtained. Based on the weakly annotated training samples, the model can automatically label the local feature region of the target, thus obtaining the more descriptive feature of the target. Experimental results show that the model can achieve high detection rate and low bit error rate of typical road targets, and the efficiency of the algorithm is improved compared with the classical algorithm.
【作者单位】：中国地质大学自动化学院;
【基金】：国家自然科学基金青年基金资助项目(61503349) 湖北省自然科学基金资助面上项目(2012FEB6407) 2016年中国地质大学校C类学术创新基地开放基金资助项目(AU2015CJ017)
【分类号】：U463.6;TP391.41

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