22 skills found
Anlin-Abishek / RealTime Face Eye IdentifierA Python-based computer vision application using OpenCV and Haar Cascades to detect faces and eyes in real-time with custom user-labeling features.
ahmetozlu / Human Computer InteractionFist, palm and hand detection & tracking for intelligent human-computer interaction game character movement control with OpenCV on Java (Processing sketchbook).
prateekvjoshi / Body Parts DetectionDetection of different body parts using Haar-like features
rgcda / HaarpsiThe Haar wavelet-based perceptual similarity index (HaarPSI) is a similarity measure for images that aims to correctly assess the perceptual similarity between two images with respect to a human viewer.
FenHua / Image Featuresfeatures extraction；artificial features；hog；haar；lbp；sift；softnms
aj1365 / DeepCNN PolsarThis code is for the paper "PolSAR Image Classification based on Deep Convolutional Neural Networks and Wavelet Transformation" that is published in the IEEE Geoscience and Remote Sensing Letters journal.
hako / Dissertation:mortar_board: :scroll: This repository holds my final year and dissertation project during my time at the University of Lincoln titled 'Deep Learning for Emotion Recognition in Cartoons'.
joyeecheung / Cascade Classifier TrainerScripts to train the OpenCV cascade classifer with Haar features for AdaBoost.
jainsee24 / Parallel Face DetectionImage segmentation is the process of dividing an image into multiple parts. It is typically used to identify objects or other relevant information in digital images. There are many ways to perform image segmentation including Thresholding methods, Color-based segmentation, Transform methods among many others. Alternately edge detection can be used for image segmentation and data extraction in areas such as image processing, computer vision, and machine vision. Image thresholding is a simple, yet effective, way of partitioning an image into a foreground and background. This image analysis technique is a type of image segmentation that isolates objects by converting grayscale images into binary images. Image thresholding is most effective in images with high levels of contrast. Otsu's method, named after Nobuyuki Otsu, is one such implementation of Image Thresholding which involves iterating through all the possible threshold values and calculating a measure of spread for the pixel levels each side of the threshold, i.e. the pixels that either fall in foreground or background. The aim is to find the threshold value where the sum of foreground and background spreads is at its minimum. Edge detection is an image processing technique for finding the boundaries of objects within images. It works by detecting discontinuities in brightness. An image can have horizontal, vertical or diagonal edges. The Sobel operator is used to detect two kinds of edges in an image by making use of a derivative mask, one for the horizontal edges and one for the vertical edges. 1. Introduction Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. 2. Needs/Problems There have been widely applied many researches related to face recognition system. The system is commonly used for video surveillance, human and computer interaction, robot navigation, and etc. Along with the utilization of the system, it leads to the need for a faster system response, such as robot navigation or application for public safety. A number of classification algorithms have been applied to face recognition system, but it still has a problem in terms of computing time. In this system, computing time of the classification or feature extraction is an important thing for further concern. To improve the algorithmic efficiency of face detection, we combine the eigenface method using Haar-like features to detect both of eyes and face, and Robert cross edge detector to locate the human face position. Robert Cross uses the integral image representation and simple rectangular features to eliminate the need of expensive calculation of multi-scale image pyramid. 3. Objectives Some techniques used in this application are 1. Eigen-face technique 2. KLT Algorithm 3. Parallel for loop in openmp 4. OpenCV for face detection. 5. Further uses of the techniques
felipecorrea / Pedestrian Haar Based DetectorHaar features based (Viola-Jones, Leinhart Optimization) pedestrian detection framework
hjlin0515 / Face Detectionbased on haar features and adaboost
amita-kapoor / Image Processing And Feature DetectionImage Processing and feature detection are the two most important areas of research in Computer Vision. In our one year project we successfully implemented various techniques and coding schemes that deal with Image Processing and Feature Detection of both still images and live video. We started with converting raw images to usable forms like grayscale, plots. We performed various mathematical operations on the image transforms like blurring (Gaussian Transform), sharpening etc. We learned to perform weighted addition of images. On both still images and live video features like face, eyes, smile, upper/lower body and full body have been detected. In this project, we used Haar Classifier to detect human face and eyes. We also employed the use of support vector machines to successfully identify human upper/lower and full body. The work can be extended to pedestrian detection in case of self-driving cars.
drahulsingh / Cypher CamCypher-Cam is a Python GUI application designed for surveillance using a webcam or surveillance camera. It includes features such as motion detection, noise detection, in/out tracking, and recording functionalities. The application has a user-friendly interface and supports a dark mode for better visibility in low-light conditions.
akshaybahadur21 / FaceDetectionA face detection module for humans 🧔♂️
alex-lechner / Face Eyes Smile DetectionA face, eyes, and smile detector using Haar-like features with OpenCV.
eechhx / Opencv Cascade TrackerTraining, detecting, and tracking a Haar Cascade in OpenCV with Python
Andreluizfc / OpenCV Haar AdaBoostAdaBoost + Haar Features Example
Droliven / FaceDetection HaarLikeFaceDetection based upon Haar-Like features.
naveenaks / Video Emotion RecognitionFacial expressions play an important role in identifying the emotional state of an individual and help others relate, understand and respond accordingly. Individuals can have different reactions to the same stimuli. This project aims to examine the emotional state of patients experiencing psychosis.The objective is to detect the various emotions of these patients, these emotions might include anger, disgust, fear, joy, sadness, surprise or neutral. This is achieved by making the patient play a game while their facial expressions are obtained through a live web camera. This is used to monitor and record their emotions as data for medical purpose. Implementing the Haar Algorithm, the frames are cropped and the face alone is procured on which grey scaling and resizing process is carried out. Now the sequence of faces obtained will be used to extract the most necessary features by a CNN - 2D(Convolutional neural network) to extract the most necessary features of each face, which will encode motion and facial expressions to predict emotion. Two sets of data are used as the dataset - Training set- the algorithm will read, or ‘train’, on this over and over again to try and learn its task, and the Testing set - the algorithm is tested on this data to see how well it works.
zeph7 / Python Opencv Face DetectorA full fledged python face detector application using Haar Cascade File containing face features
