Autonomous RC Car using Neural Networks, Python and Open CV

Snapchat-like Face Filters in OpenCV

Collection of HAAR and LBP cascades designed to recognize various street signs

Vision Based Intelligent Human-Computer Interaction Game: Control the game character's velocity through your fist or palm(hand) movement! Haar-Cascade Classifier was used for fist and palm(hand) detection. Game was developed with OpenCV on Java (Processing sketchbook)!

A complete collection of Haar-Cascade files. Every Haar-Cascades here!

IOS application for object detection using Haar feature-based cascade classifiers in OpenCV

Vehicle detection and tracking and speed estimation using opencv

A parallelised facial recognition program written from scratch in C with minimal dependencies

A simple python program to detect object using Haar Classifiers

A Facial Features Recognition using Opencv and Haar-Cascades

👨‍👩‍👦‍👦 Piplcount - Count how many humans are in the scene (from cam feed or video file).

A face, eyes, and smile detector using Haar-like features with OpenCV.

A lightweight, real-time application to invigilate an exam automatically without requiring any manual invigilator, expensive hardware or data-set training. Suited for users with lesser bandwidth.

Face Detection and Recognition

Detects faces with pretrained OpenCV Haar classifiers, with OpenCV and Python.

The interface of the autonomous car with the surroundings must be similar to that of human way of interaction. Humans use their eyes as a source of vision and then processes the visual signals in his/her brain and takes the necessary action accordingly. Similarly the autonomous car uses a camera as a visual source to know its surrounding, path etc. and uses the image processing techniques on the images received from the camera. This processing takes place on a minicomputer (RASPBERRY PI). After image processing, control instructions are passed on to the driving motors which helps in steering the vehicle accordingly.

Haar classifier to detect Bodna or Lota in images or Video.

Single Frame / Real-time face recognizing with eigen-faces

Human face identification has been a testing issue in the regions of picture preparing and patter acknowledgment. Another human face location calculation by crude Haar course calculation joined with the refreshed changes are to be examined.First, pictures of individuals are handled by a crude Haar course classifier, almost without wrong human face dismissal (low rate of false negative) yet with some wrong acknowledgment (false positive). Also, to dispose of these wrongly acknowledged non-human faces, a powerless classifier in light of face skin tint histogram coordinating is connected and a dominant part of non-human countenances are evacuated. Next, another frail classifier in view of eyes identification is attached and some leftover non-human appearances are resolved and dismissed. At last, a mouth recognition task is used to the rest of the non-human appearances and the false positive rate is additionally diminished.

Face Recognition with VGG and Resnet model by using Transfer learning.

Detecta el plexo branquial desde imgenes de ultrasonido del cuello

OpenCV prototype linked integrate frameworks using HAAR Classification and DLib & CLM Face Detection models composed by a collection of miscellaneous Machine Learning, Computer Vision, Image Processing, and Linear Algebra algorithms.

OpenCV detection based security cam using node.js Detects intruders from the webcam video and saves images of them.