搜索资源列表
vgrabbj
- 视频捕捉，用一个抓图应用程序进行测试，进入/test 目录，敲入./vgrabbj -f /tmp/1.jpg。应该会在/tmp 目录下生成一张摄像头拍摄的图片了。-video capture with a screen in application testing, access / test directory, Knock. / vgrabbj-f / tmp/1.jpg. Should the / tmp directory generated a camera shooting p
filter20060808
- 一个过滤器脚本，需要DX9支持，欢迎测试，有问题告诉我-a scr ipt filters need DX9 support and welcome testing, and it is telling me
hardh264
- 一个硬件H264编码的VHDL源码，用于FPGA开发，适合IP摄像头等视频设备输出数据的编码。用Xilinx工具测试过，但代码不只是用于Xilinx。-A hardware h264 video encoder written in VHDL suited to IP cameras and megapixel cameras. Designed to be synthesized into an FPGA. Initial testing is using Xilinx tools
Motion_Detection
- 基于.net2.0的视频或摄像头中的运动人物检测程序，可以根据在线的摄像头进行判别-Based. Net2.0 video or camera movement of people in the testing process can be carried out according to determine camera online
VideoCapture
- 一个功能很强大的视频捕获和视频播放程序，能实现抓拍和动态检测。还可以设置字幕。-A feature very powerful video capture and video playback program, able to capture and dynamic testing. You can also set the subtitles.
philip
- 我做的视频监控测试程序，可以采集摄像头。。Ｃ#方面的可以参考下-I do video surveillance testing program, the camera can capture. . C# can refer to the following terms
video segement
- 应用于新闻视频的镜头检测，可以检测闪光，能够实现准确的切变镜头分割。-News video from the camera used in testing, can detect the flash, to achieve an accurate shot segmentation shear.
video-based-traffic-monitoring
- 本文重点讲了在摄像头视野内的多辆车的监控和跟踪。基于特征检测的层次结构和融合，我们在本文中提出一个新的车型检测框架。-This article focuses on about the monitoring and tracking of vehicles in the camera field of view. Based on the hierarchy of the feature detection and integration in this paper, we propose a
Video4
- 基于VC6.0+VFW下的视频采集，可以拍照，预览和录像。功能简单，适合入门。在笔记本（带摄像头）下测试通过。-For based on video capture VC6.0+VFW, can take pictures, preview and video. Simple functions, and is suitable for entry. Testing via laptop (with a camera).
CamSnap-Demo-2
- Demo program for testing Webcam snapshot connection
subcide
- Testing Video Camtasia
GMM
- 针对摄像机固定下的复杂背景环境，对采集到的视频图像的图像数据用混合高斯背景建模方法实现前景/背景分割，实现运动目标检测和跟踪。在进行前景检测前，先对背景进行训练，对图像中每个背景采用一个混合高斯模型进行模拟，每个背景的混合高斯的个数可以自适应。然后在测试阶段，对新来的像素进行GMM匹配，如果该像素值能够匹配其中一个高斯，则认为是背景，否则认为是前景。由于整个过程GMM模型在不断更新学习中，所以对动态背景有一定的鲁棒性。最后通过对一个有树枝摇摆的动态背景进行前景检测，取得了较好的效果。-For c
homograph
- 利用单应变换的方法对视频序列中的前景进行检测-The method of using a single video sequence should transform the prospects for testing
CameraTest2
- Android Camera Testing Project