面向三维重建的自适应步长视频关键帧提取

Adaptive Step Size Video Key Frame Extraction for 3D Reconstruction

为解决视频帧数量多、易出现模糊帧造成的三维重建计算量过大、三维模型误差较大问题,提出一种自适应步长视频关键帧提取算法。该算法基于多通道直方图欧式距离计算图像相似性,利用拉普拉斯梯度函数计算图像清晰度,根据视频帧之间的相似性动态确定关键帧提取步长,通过清晰度检测规避模糊帧。在高清匀速视频和变速模糊视频上进行实验,并与当前多种视频关键帧提取算法进行比较。实验表明,该算法显著缩短了关键帧的提取时间,重建的三维模型精度更优。

In order to solve the problem of large calculation of 3D reconstruction and large error of 3D model caused by the large number of video frames and easy to appear fuzzy frames,an adaptive step video key frame extraction algorithm is proposed.The algorithm calculates the image similarity based on the multi-channel histogram Euclidean distance,and the image sharpness based on the Laplacian gradient function.The key frame extraction step is dynamically determined according to the similarity between video frames,and the fuzzy frame is avoided through the sharpness detection.Experiments are carried out on high-definition constant speed video and variable speed blurred video.Com-pared with the current multiple video key frame extraction algorithms,the key frame extraction time of the proposed algorithm is reduced signif-icantly,and the accuracy of the reconstructed 3D model is better.