نتایج جستجو برای: face detection and tracking
تعداد نتایج: 16971321 فیلتر نتایج به سال:
The main idea behind this project is to develop a system which can detect drowsiness of the driver and giving an indication in the form of alarm. Since a large number of road accidents occur due to the driver drowsiness, here we are proposing a new transportation system which will reduce the accidents. This system will monitor the driver’s eyes using camera and face detection which is very impo...
Face detection is a key problem in building automated systems that perform face recognition/ verification, modelbased image coding, face tracking, and surveillance. Two algorithms for face detection based on either support vector machines or maximum likelihood estimation are described and their performance is tested on a collection of single images from the M2VTS database that depict one fronta...
This paper presents an audio-video surveillance system for the automatic surveillance in public transport vehicle. The system comprises six modules including in particular three novel ones: (i) Face Detection and Tracking, (ii) Audio Event Detection and (iii) Audio-Video Scenario Recognition. The Face Detection and Tracking module is responsible for detecting and tracking faces of people in fro...
In this paper we propose a simple and efficient eye detection method for face detection tasks in color images. The algorithm first detects face regions in the image using a skin color model in the normalized RGB color space. Then, eye candidates are extracted within these face regions. Finally, using the anthropological characteristics of human eyes, the pairs of eye regions are selected. The p...
this paper presents a comparison study between the multilayer perceptron (mlp) and radial basis function (rbf) neural networks with supervised learning and back propagation algorithm to track hand gestures. both networks have two output classes which are hand and face. skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...
This paper presents an annealed neural network based method for face detection. We present a robust algorithm that improves face detection and tracking in video sequences by using geometrical facial information and an annealed neural network verification. A new method, a three-face reference model (TFRM), and its advantages, such as, allowing for a better match for face verification, will be di...
In this paper a novel face tracking approach is presented where optical flow information is incorporated into the Viola-Jones face detection algorithm. In the original algorithm from Viola and Jones face detection is static as information from previous frames is not considered. In contrast to the ViolaJones face detector and also to other known dynamic enhancements, the proposed face tracker pr...
in this study, a simple, rapid and selective method was developed for the determination of dexamethasone. the proposed method is based on inhibitory effect of dexamethasone on the oxidation of orange-g by bromate in sulfuric acid media. the reaction was followed spectrophotometrically at 478.5 nm (?max). under optimum experimental conditions, (72.6 ?mol l-1 of orange-g, 0.76 mol l-1 of h2so4, 0...
Human or face tracking in a diverse environment is very important for various applications in computer vision, especially for video surveillance. Usually, a color cue offers many advantages over motion or geometric information which cannot robustly handle partial occlusion, rotation, scale and resolution changes. In this paper, we present a robust face tracking system by employing a color-based...
Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of Oriented Gradients, i.e. HOG, features. A K-mean clustering technique is used in a cascade of HOG feature classifiers to detect faces. The evaluatio...
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