基于视觉显著性的车载单目相机自运动估计及前车尺度估计方法

A method based on visual saliency for vehicle-mounted monocular camera ego-motion estimation and vehicle scale estimation

提出一种基于视觉显著性的车载单目相机自运动估计及前车尺度估计方法。首先,针对车载相机自运动估计,通过视觉显著性计算方法检测并去除含有噪声的单目图像序列中的运动目标,同时考虑图像的纹理区域和平滑区域,利用加权显著图保留有用特征点,进而对车载相机进行鲁棒的自运动估计。其次,将前车距离转化为前车尺度估计问题,通过描述子匹配与李代数中正则化的强度匹配相结合的方法最小化损失函数,通过设计视觉注意力机制选择有纹理无遮挡的图像块,并对选定的图像块中的像素赋权以减轻被噪声破坏像素的影响,从而实现鲁棒、准确的尺度估计。最后,利用多个具有挑战性的数据集对所提方法进行分析验证。结果表明,单目相机自运动估计方法达到了基于立体相机方法的水平,前车尺度估计方法在充分发挥强鲁棒性优势的同时保证了预测精度。

A method based on visual saliency for ego-motion estimation and scale estimation of the vehicle in front was proposed.Firstly,for the ego-motion estimation of vehicle-mounted camera,the visual saliency calculation method was used to detect and remove moving objects in the monocular image sequence containing noise.While considering the im-age texture and smooth region,the weighted saliency map was used to retain useful feature points,to improve the robust-ness of ego-motion estimation.Secondly,the distance of the vehicle in front was converted into a vehicle scale estimation,by integrating descriptor match and the strength of regularization match of the lie algebra to minimize loss function.The visual attention mechanism was used to get texture image block without shade,and the pixel in the image block weight to mitigate the effects of destroyed by noise pixel,so as to realize the robust and accurate scale estimation.Finally,several challenging datasets were used to analyze and verify the proposed method.The results show that the monocular camera ego-motion estimation method reaches the level of the stereo camera-based method,and the vehicle scale estimation me-thod ensures the prediction accuracy while giving full play to the advantages of strong robustness.