CAJ | 학술논문

针对传统视频稳定算法存在的前景局部运动影响全局运动估计精度的难点问题，提出了一种可靠特征集合匹配的高精度视频稳定算法。算法首先利用距离筛选法和金子塔模型提高特征匹配精度，然后利用MLESAC算法剔除运动物体上的无效特征，最后将保留下来的精确匹配特征带入仿射运动模型求出全局运动矢量，并据此对视频帧进行运动补偿以实现稳定视频的目的。实验结果表明，相比于传统基于特征匹配的视频稳定算法，改进全局运动估计算法提高了视频稳定的精度。
침대전통시빈은정산법존재적전경국부운동영향전국운동고계정도적난점문제，제출료일충가고특정집합필배적고정도시빈은정산법。산법수선이용거리사선법화금자탑모형제고특정필배정도，연후이용MLESAC산법척제운동물체상적무효특정，최후장보류하래적정학필배특정대입방사운동모형구출전국운동시량，병거차대시빈정진행운동보상이실현은정시빈적목적。실험결과표명，상비우전통기우특정필배적시빈은정산법，개진전국운동고계산법제고료시빈은정적정도。
Aiming at the the problems of traditional video stabilization that the global motion estimation accuracy is reduced by the local motion. A highly accurate video stabilization algorithm based on feature matching was put for-ward. Firstly screening method based on distance and Gaussian pyramid model was used to improve the feature matc-hing accuracy, and then MLESAC algorithm was used to remove the features from local motion object. Finally, the global motion estimation vector based on affine model was computed by accurately matching preserved features and the trembling image was compensated to stabilize the image sequence according to the global motion estimation vector. The experiment results show that compared with the traditional feature-based matching video stabilization algorithm, the motion estimation algorithm improves the video stabilization accuracy.