WANG XIN's repositories
abnormal-activity-detection
Automatically exported from code.google.com/p/abnormal-activity-detection
Abnormal-Detection-50videos
Anomaly detection using C++ and OpenCV library (not yet implemented)
actiongraph
Action recognition based on action graph, which describes the spatio-temporal relationship between dense trajectory clusters. The program consists of three parts: 1) Dense trajectory extraction based on Wang Heng's CVPR paper; 2) Action graph construction; 3) Video classification based on action recognition.
C4-Real-time-pedestrian-detection
Real-Time Human Detection Using Contour Cues
camshiftKalman
An object tracking project using camshift and Kalman Filter based on OpenCV
crowd_group_profile
Matlab code for our CVPR 2014 work "Scene-Independent Group Profiling in Crowd".
Image-feature-detection-using-Phase-Stretch-Transform
PST or Phase Stretch Transform is an operator that finds features in an image. PST implemented using MATLAB here, takes an intensity image I as its input, and returns a binary image out of the same size as I, with 1's where the function finds sharp transitions in I and 0's elsewhere.
multiple-tracking-master
Contains the background subtraction + multiple object tracking software we developed.
object-tracking
Object Tracking For Vehicles and Pedestrians
object_tracking_2D
Edge Based Tracking library
ObjectTracker
Multiple object tracking with a fixed, overhead camera using background subtraction and Kalman filters
OpenTLD
A C++ implementation of OpenTLD
OpticalFlow
Real-Time Optic Flow Computation with Variational Methods, faster than OpenCV
Pedestrian-Detection-Project
Pedestrian Detection Project Codes and Documentations
Pedestrian_Counter
C++ application using OpenCV able to detect and count pedestrians and cyclists
PedestrianDetection
计算机视觉课程设计作业，检测图像中的行人目标并跟踪。
pedsim
standalone pedsim library (pedestrian simulator using social force model)
SnapVision
SnapVision will develop a video processing application that runs on the Snapdragon™ SoC development board. The application will process a video stream and stitch adjacent frames into a mosaic. There are many possible use cases for this project. Some examples include: Aiding in search and rescue operations in hostile environments. Looking into population density in order to solve communication issues, heavy traffic concentrations, etc. Improving crop yield by identifying areas with poor irrigation or disease. Finding broken fences or equipment. Searching incoming weather patterns for abnormal behavior. After looking at the viability of both MATLAB and C++, SnapVision decided to go with C++ and the OpenCV library to complete the image stitching process. Further, we will discuss the project with our chosen subject matter expert to gain additional knowledge about the current research regarding image processing techniques. The next step in the approach after the application is developed and tested would be to run it on the DragonBoard 410c provided by Qualcomm.
ssf
Smart Surveillance Framework
tfAlexNet
this is an implementation of alexnet with tensorflow. Run the train.py for training, and test.py for testing. You only need to config the picture folder path
The-Realtime-Abnormal-Event-Detection-Project
The Realtime Abnormal Event Detection Project
TrafficCounter
Traffic Counter with C++ and OpenCV, using Kalman Filter
VIBE
VIBE Background Subtractior
VoIP-Statistics
Simulate abnormal traffic patterns for analyzing detection methods