Combining background information and a top-down model for computing salient objects

Pedestrian detection is a fundamental problem in video surveillance. An overwhelming majority of existing detection methods are based on sliding windows with exhaustive multi-scale scanning over the whole frame images which can achieve good accuracy but suffer from expensive computational cost. To reduce the complexity significantly while keeping high accuracy, in this paper, we propose an effective and efficient pedestrian detection method based on sliding windows with well-designed multi-scale

通过该蛇皮项目的实战，了解HBase的应用场景和如何使用JAVA-API来完成对于增删改查数据的需求

留个备份,有需要的拿去吧

这个插件包含了 main.js（popup页面使用的js） 跟 background.js（后台） 之前的通信 main.js（popup页面使用的js） 跟 content.js（注入到dom的js） 之前的通信 background.js 跟 cntent.js 之前的通信

backgroundworker+process进度条完整解决方案，以测试通过

GMM算法经典论文，opencv中的GMM算法应该就是参考这边文章。自己做的中文翻译pdf也附在了里面

Improved adaptive Gausian mixture model for background subtraction，经典的GMM算法改进论文，opencv中的GMM改进算法有参考这篇文章，把自己的翻译也附在里面