搜索资源列表
Adaptive-background-mixture-models-
- 在目标检测中有关高斯背景建模方法的实现和国际上先进方法的介绍-Adaptive background mixture models for real-time tracking(高斯背景建模方法)
checking
- 目标检测与跟踪,讲述了目标检测方法和跟踪方法,是当前的先进技术-Target detection and tracking
Kumar_cvpr12
- 这篇文章主要采用“Client-Server based Vote Transfer”的方法进行对移动目标检测。是2012年CVPR中的文章。-The article " Client-Server based Vote Transfer" method to detect moving targets. CVPR 2012 article.
A-self-organizing-approach-
- 本文章主要是研究前景检测中的移动目标检测的方法。以此来实现相关功能-A self-organizing approach to background subtraction for visual surveillance applications
Survey-of-pedestrian-detection-
- 分析行人移动目标检测的相关外文文献,实现了基于背景建模的相关方法-Survey of pedestrian detection for advanced driver assistance systems
Smal-l-Target--Detection
- 提出了一种新的基于小波包变换 和偏斜度的检测方法。该方法利用小波包对图像进行多尺度分解,解决了高频段分辨率低的问题; 并提出了一个基于偏斜度的高斯判别准则,用于对小波包分解系数进行高斯性检验,最终得到了 小目标的精确检测-The wavelet packets were applied to decompose the image into pyramid subbands at different scales and solve the problem of the high
ssd-method-for-object-detection
- ssd是当前目标检测领域的最先进的研究方法,也是今年CVPR会议的最新成果-Ssd is the most advanced research method in the current target detection field and the latest achievement of this year s CVPR conference