Projects tagged ‘computervision’ and ‘detection’

OpenVss is a system level video surveillance software based on the Video Analysis Framework (VAF) technology, for multi-cameras platform, multi-analyzer modules, and multi-cores/processors ... [More] architecture with recording, alerting, searching and playback supported system. It has been designed and developed at Prince of Songkla University in the Department of Computer Engineering, by the iSys Research Laboratory, Thailand. How to setup VsEnterprise Server How to setup VsEnterprise Client How to config VsEnterprise VsMonitor Demo VsLive Demo VsPlayback Demo1 VsPlayback Demo2 [Less]

Java implementation on speeded up robust features SURF. SURF (Speeded Up Robust Features) is a robust image descriptor, first presented by Herbert Bay et al. in 2006, that can be used in computer ... [More] vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images. As basic image features it uses a Haar wavelet approximation of the determinant of Hessian blob detector. More about surf on http://en.wikipedia.org/wiki/SURF Currenty this project is refactored version of http://processingsurf.altervista.org/ where the dependency of Processing is removed. The general idea is to create java SURF lib that can be easily integrated into excising projects also to give various example sub projects interesting usage of SURF for machine learning and computer vision projects [Less]

Detection, tracking, segmentation, and delineation of neurons in microscopic images and videos. Conferences Wiki

OpenSURF is a clean, unintrusive SURF feature extraction library written in C++ with OpenCV. The OpenSURF library was originally written in Visual Studio 2005, although a linux compatible makefile ... [More] has been contributed and is available in the SVN directory. Should you wish to contribute to the project please email your Google Code id and I will arrange SVN access. Please mail any comments/questions/suggestions to cae.dev@gmail.com [Less]