Developed an iOS application for detecting pedestrian based on computer vision and machine learning with C++. Collected dataset, Extracted features based on Haar-like, HOG and LBP algorithm under OpenCV and trained classifiers. Implemented Non-maximum Suppression algorithm to improve accuracy。 Utilized pre-image-processing, Armadillo library and GPU to accelerate the speed of processing. This application is able to be used in iPhone, iPad and any iOS devices and detect pedestrians accurately in real video frames.
-
Notifications
You must be signed in to change notification settings - Fork 1
Developed an iOS application for detecting pedestrian based on computer vision and machine learning with C++. Collected dataset, Extracted features based on Haar-like, HOG and LBP algorithm under OpenCV and trained classifiers. Implemented Non-maximum Suppression algorithm to improve accuracy。 Utilized pre-image-processing, Armadillo library and…
XingchenYu/pedestrian_detection_iosapp
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Developed an iOS application for detecting pedestrian based on computer vision and machine learning with C++. Collected dataset, Extracted features based on Haar-like, HOG and LBP algorithm under OpenCV and trained classifiers. Implemented Non-maximum Suppression algorithm to improve accuracy。 Utilized pre-image-processing, Armadillo library and…
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published