搜索资源列表
Linux2.4内核防火墙的连接跟踪技术
- Linux2.4内核防火墙的连接跟踪技术-Linux kernel firewall connectivity tracking technology
KernelTracking
- A new approach toward target representation and localization, the central component in visual tracking of non-rigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kern
KernelObjectTrack
- Kernel Object Tracking算法实现代码,自己本科毕设!-Kernel Object Tracking algorithm code, we completed the set up their own!
generalized
- Generalized Kernel-based Visual Tracking的源代码,对研究目标跟踪的学者很有用-The source code of Generalized Kernel-based Visual Tracking
Windows_mantis
- Windows下搭建mantis Git 是用于 Linux 内核开发的版本控制工具。与常用的版本控制工具 CVS, Subversion 等不同, 它采用了分布式版本库的方式,不必服务器端软件支持,使源代码的发布和交流极其方便。 Git 的速度很快,这对于诸如 Linux kernel 这样的大项目来说自然很重要。 Git 最为出色的是它的合并跟踪(merge tracing)能力。 作为开源自由原教旨主义项目,Git 没有对版本库的浏览和修改做任何的权限限制。 它只适用于 Li
nftest[1]
- 主要介绍基于Linux内核的HyperCuts算法和原理及其实现-This paper documents the results of the performance testing of netfilter, the firewalling subsystem of the Linux kernel. We compared the performance of two different hardware configurations and meas
tms3206713
- 关于DSP TMS3206713的一些资料,包括DSP C6000的反汇编,dsp实时内核在视频目标跟踪系统中的应用,DSP算法标准及其应用-Some information about the DSP TMS3206713, including DSP C6000 disassembly, dsp real-time kernel in the video tracking system, DSP Algorithm Standard and its application
Seg_By_MeanShift
- 均值漂移Mean Shift算法是一种基于核密度估计的处理方法,被广泛用于图像降噪,分割和目标跟踪中,本代码是图像分割实现。-Mean Shift algorithm is a kernel density estimation based approach is widely used for image noise reduction, segmentation and target tracking, the code is to achieve image segmentation.
04618836
- 有关于meanshift核函数带宽变更不错的跟踪算法-Change a good tracking algorithm About meanshift bandwidth of kernel function
qpc_4.5.02
- QP量子编程最新源码 QP: Quantum Programming QP是一个通用的事件驱动框架,面向MCU,面向并发的层次式状态机模型。 QP包含了1个轻量级的QK(Quantum Kernel)。 QEP:Quantum Event Processor是一个通用的,可移植的,可重用的状态机引擎。 QEP允许你直接把UML样式的状态图映射为代码。 QEP提供了传统的简单平面状态机和层次式状态机。QEP可以直接操作事件队列和事件分发机制。 QF是一个通用的,事件驱动
Kernel-particle-filter
- 基于核粒子滤波的视觉跟踪,采用核密度和粒子滤波结合,进行视觉图像跟踪-Nuclear density and particle filter a nuclear particle filter-based visual tracking, visual image tracking
xt_connbytes
- Kernel module to match connection tracking byte counter for linux
xt_state
- Kernel module to match connection tracking information for linux.
[kimi]FGT
- 实现了 Changjiang Yang, etc. “Real-Time Kernel-Based Tracking in Joint Feature-Spatial Spaces”, Technical Reports from UMIACS, 2004 中的FGT算法。-The code for FGT(Fast Gauss Transform) from: Changjiang Yang, etc. “Real-Time Kernel-Based Tracking in Joint Fea
meanshift-pingyizhuizong
- meanshift均值平移跟踪算法中核函数窗宽的自动选取代码,根据目标大小变化核窗宽,使得当目标出现大小变化时准确跟踪到目标中心-Meanshift mean shift tracking algorithm in the kernel function of window width automatically select code, according to the target size change window width, that when the target size cha
m10
- 背景建模是实现运动目标检测与跟踪的关键技术之一。在实时视频监控系统中,对背景建模算法的运行时间及所提取出的背景图像的实时性有很高的要求,针对这一问题,提出了一种基于切比雪夫不等式的自适应阈值背景建模算法。算法利用切比雪夫不等式计算像素点色度变化的概率估计值,提出了一种自适应阈值分类方法,它将像素点快速分类为前景点、背景点及可疑点,再利用核密度估计方法对可疑点进行进一步分类,最后利用背景更新算法提取实时背景图像。实验结果证明,该算法能快速有效地区分特征明显的背景点与前景点,提高了背景图像提取的速
Mean-Shift-kernel
- MeanShift跟踪算法中核函数窗宽的自动选取程序-Mean-Shift tracking algorithm in the kernel function automatically selects the window wide program
CreateProcessNotify
- NT/2K provides a set of APIs, known as "Process Structure Routines" [2] exported by NTOSKRNL. One of these APIs PsSetCreateProcessNotifyRoutine() offers the ability to register system-wide callback function which is called by OS each time when a new
meanshift,tracking
- meanshift均值平移跟踪算法中核函数窗宽的自动选取代码,根据目标大小变化核窗宽,使得当目标出现大小变化时准确跟踪到目标中心(Meanshift mean shift tracking algorithm, kernel function window width automatic selection code, according to the target size changes in the width of the nuclear window, so that when the
kafbox-1.4
- Kernel自适应滤波器算法是基于Kernels的在线自适应回归算法。非常适合非线性滤波,跟踪和回归。该工具箱包括算法,演示和性能比较工具(Kernel adaptive filtering algorithms are online and adaptive regression algorithms based on kernels. They are suitable for nonlinear filtering, prediction, tracking and nonlinear r