Optical flow algorithms
Optical flow algorithms are used in videos to track features across successive frames. Let's say you want to track a particular object in a video. Running a feature extractor on each frame would be computationally expensive; hence, the process would be slow. So, you just extract the features from the current frame, and then track those features in successive frames.
Optical flow algorithms are heavily used in video-based applications in computer vision. The optflow module contains all the algorithms required to perform optical flow. There is also a module called tracking that contains more algorithms that can be used to track features.
推薦閱讀
- LibGDX Game Development Essentials
- Building Computer Vision Projects with OpenCV 4 and C++
- Python絕技:運用Python成為頂級數據工程師
- Greenplum:從大數據戰略到實現
- App+軟件+游戲+網站界面設計教程
- Visual Studio 2015 Cookbook(Second Edition)
- 卷積神經網絡的Python實現
- Learning JavaScriptMVC
- Power BI智能數據分析與可視化從入門到精通
- 大數據分析:數據倉庫項目實戰
- openGauss數據庫核心技術
- 商業智能工具應用與數據可視化
- 改進的群智能算法及其應用
- 云工作時代:科技進化必將帶來的新工作方式
- 標簽類目體系:面向業務的數據資產設計方法論