融合图像语义的动态视频拼接方法

针对当前视频拼接方法仅考虑图像低阶几何特征而没有考虑图像高阶语义特征的问题,提出融合图像高阶语义信息的视频拼接方法,并采用多线程编程方式提高拼接速度。主要贡献包括:①自适应动态视频拼接系统框架;②融合语义的高效特征匹配算法;③融合语义的视频拼接质量评价算法。为验证提出算法的有效性,使用车载摄像机在校园环境内进行动态视频拼接实车实验。实验结果显示,相比于传统方法,该匹配算法正确率提升了50%左右,拼接评价算法更符合人眼视觉,方法的拼接质量提升了25%左右,具有较高的鲁棒性与准确性。

Dynamic video stitching method embracing image semantics

Aiming at the problem that only low order geometric features of images are considered in the current video stitching methods without consideration of the high order semantic features of images, we propose a dynamic video stitching method embracing image semantics, which adopts the multi threaded programming for accelerating stitching speed. The main contributions are an adaptive dynamic video stitching system framework, an efficient feature matching algorithm embracing semantics image, and video stitching quality evaluation algorithm embracing semantics. The vehicle mounted cameras are applied in the experiment of dynamic video stitching in campus environment for verifying the effectiveness of the proposed algorithm. Obviously, compared with the traditional algorithm, the accuracy rate of new matching algorithm dramatically increases by 50% , the result evaluated by new stitching qulity evaluation algorithm are also more suitable for the human visual sense, and the stitching quality of the proposed stitching method increases by about 25% with remarkable robustness and accuracy.