OpenCV3.0 3.1版本号的改进

摘要

OpenCV如今更新到了3.1版本号，相对OpenCV2有了非常大改进，当中对于硬件加速，移动开发（IOS，android）的支持成为亮点。

新版的OpenCV採用了内核+插件的架构模式，总体上更加易于扩展。

当中最与时俱进的特点就是支持最新的 Windows 和 OS X 操作系统和最新的开发工具 (VS2015 和 Xcode 7)，支持 Andorid 5。软件的更新换代推动硬件更新，并进一步推动摩尔定律，相信OpenCV的新版会带动很多其它人更新Win10，vs2015等等革命性的产品，同一时候购买能够并行加速的N卡。在软硬件层面获取性能的提升从而产出科研成果或者优秀的应用。

（一）google编程之夏

OpenCV基础库的更新：得益于google summer of code更新了一大批有意思的项目

google编程之夏的介绍：https://linuxtoy.org/archives/mentor-in-google-summer-of-code-1.html

- Omnidirectional Cameras Calibration and Stereo 3D Reconstruction – opencv_contrib/ccalib module (Baisheng Lai, Bo Li)
- Structure From Motion – opencv_contrib/sfm module (Edgar Riba, Vincent Rabaud)
- Improved Deformable Part-based Models – opencv_contrib/dpm module (Jiaolong Xu, Bence Magyar)
- Real-time Multi-object Tracking using Kernelized Correlation Filter – opencv_contrib/tracking module (Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
- Improved and expanded Scene Text Detection – opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
- Stereo correspondence improvements – opencv_contrib/stereo module (Mircea Paul Muresan, Sergei Nosov)
- Structured-Light System Calibration – opencv_contrib/structured_light (Roberta Ravanelli, Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
- Chessboard+ArUco for camera calibration – opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
- Implementation of universal interface for deep neural network frameworks – opencv_contrib/dnn module (Vitaliy Lyudvichenko, Anatoly Baksheev)
- Recent advances in edge-aware filtering, improved SGBM stereo algorithm – opencv/calib3d and opencv_contrib/ximgproc (Alexander Bokov, Maksim Shabunin)
- Improved ICF detector, waldboost implementation – opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
- Multi-target TLD tracking – opencv_contrib/tracking module (Vladimir Tyan, Antonella Cascitelli)
- 3D pose estimation using CNNs – opencv_contrib/cnn_3dobj (Yida Wang, Manuele Tamburrano, Stefano Fabri)