scholarly journals Real–Time Eye Tracking and Iris Localization

2012 ◽  
Author(s):  
Husniza Razalli ◽  
Rahmita Wirza O. K. Rahmat ◽  
Ramlan Mahmud
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Vision System ◽  
Main Task ◽  
Circle Fitting ◽  
Eye Tracker ◽  
Eye Detection ◽  
Iris Localization ◽  
Point Detection ◽  
Human Eyes

Masalah sistem pengesanan mata yang tegar tanpa sebarang gangguan adalah satu isu yang penting dan mencabar di dalam bidang visi komputer. Masalah ini bukan hanya mengurangkan masalah dalam carian ciri–ciri paras rupa untuk proses pengecaman tetapi juga boleh digunakan untuk memudahkan tugas pengenalpastian dan interaksi antara manusia dan sistem komputer. Walaupun kebanyakan hasil kerja terdahulu telah pun mempunyai keupayaan menentukan lokasi mata manusia tetapi objektif utama rencana ini bukan tertumpu kepada pengesanan mata sahaja. Objektif kajian adalah untuk merekabentuk sebuah sistem masa nyata dan terperinci, iaitu sistem pengesanan muka berskala dengan ciri–ciri petunjuk pergerakan mata berdasarkan pergerakan anak mata (iris) dengan mengunakan teknik penempatan yang terhasil daripada teknik pemprosesan imej dan teknik muatan bulatan. Hasil daripada kajian ini telah pun berjaya diimplimentasikan menggunakan kamera web dengan ralat yang minimum. Kata kunci: Pengesanan mata masa nyata; penempatan anak mata; pemprosesan imej; pengesanan bucu; muatan bulatan Robust, non–intrusive human eye detection problem has been a fundamental and challenging problem for computer vision area. Not only it is a problem of its own, it can be used to ease the problem of finding the locations of other facial features for recognition tasks and human–computer interaction purposes as well. Many previous works have the capability of determining the locations of the human eyes but the main task in this paper is not only a vision system with eye detection capability. Our aim is to design a real–time face tracker system and iris localization using edge point detection method indicates from image processing and circle fitting technique. As a result, our eye tracker system was successfully implemented using non–intrusive webcam with less error. Key words: Real–time face tracking; iris localization; image processing; edge detection; circle fitting

A Robotic Facial Expression Recognition System Using Real-Time Vision System

2008 ◽  
Vol 381-382 ◽  
pp. 375-378
Author(s):  
K.T. Song ◽  
M.J. Han ◽  
F.Y. Chang ◽  
S.H. Chang
Keyword(s):  
Image Processing ◽  
Facial Expression ◽  
Real Time ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Vision System ◽  
Recognition System ◽  
Expression Recognition ◽  
On Line ◽  
Processing Platform

The capability of recognizing human facial expression plays an important role in advanced human-robot interaction development. Through recognizing facial expressions, a robot can interact with a user in a more natural and friendly manner. In this paper, we proposed a facial expression recognition system based on an embedded image processing platform to classify different facial expressions on-line in real time. A low-cost embedded vision system has been designed and realized for robotic applications using a CMOS image sensor and digital signal processor (DSP). The current design acquires thirty 640x480 image frames per second (30 fps). The proposed emotion recognition algorithm has been successfully implemented on the real-time vision system. Experimental results on a pet robot show that the robot can interact with a person in a responding manner. The developed image processing platform is effective for accelerating the recognition speed to 25 recognitions per second with an average on-line recognition rate of 74.4% for five facial expressions.

Image Analysis

2013 ◽  
pp. 1-14
Author(s):  
Detlev Droege
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Eye Tracking ◽  
Real Time ◽  
Basic Knowledge ◽  
Eye Tracker ◽  
Tracking Systems ◽  
Program Code ◽  
Time Performance

This chapter focuses on the image processing part of eye tracking systems. Basic knowledge of image processing is assumed. After an overview of the possible input images and some remarks on preprocessing of the images, we will focus on the detection relevant features such as pupils and glints. The last part of this chapter focuses on estimating positions of these features. It is not possible to present a comprehensive solution for an eye tracker in this chapter; however, we will indicate possible yet simplified methods in the different steps of processing and demonstrate how images can be processed to obtain real-time performance. The program code is given in Matlab (Octave) language for clarity.

A Knowledge-Based Real-Time Vision System for Monitoring the Inside of a Fluid Bed Heat Exchanger Chamber

2018 ◽  
Vol 28 (09) ◽  
pp. 1249-1265
Author(s):  
HyungJun Kim
Keyword(s):  
Image Processing ◽  
Heat Exchanger ◽  
Real Time ◽  
Vision System ◽  
Thermal Power ◽  
Experimental Results ◽  
Image Analysis System ◽  
Real Time Monitoring ◽  
Knowledge Based ◽  
Fluid Bed

In this paper, we present a vision system with a special camera for knowledge-based real-time monitoring of the inside of a fluid bed heat exchanger (FBHE) chamber in a thermal power plant. With the proposed system, it is possible to monitor the internal flux condition and analyze the inner temperature of a chamber. Due to the fact that the mixture of coal and sand inside a chamber flows by very quickly, there is an immense amount of smoke and dust, which make it difficult to capture images and analyze an existing system. An adaptive average method is proposed here to observe the background internal environment of an FBHE chamber. The experimental results show that real-time monitoring is possible, even under hot and dusty conditions. Preliminary experimental results confirm expectations about the possibility and effectiveness of the developed device for commercialized real-time monitoring systems. They demonstrate that a single camera with embedded image processing software can concurrently analyze the degree of fluidization of a mixture and the temperature of the chamber inside, even in extremely harsh and hazardous conditions. We aim to eventually develop an image analysis system that combines image processing and knowledge engineering techniques.

Real-Time Unwrapping and Rectification of High-Resolution Catadioptric Panoramic Video during Non-Stationary Moving

2014 ◽  
Vol 668-669 ◽  
pp. 1098-1101
Author(s):  
Jian Wang ◽  
Zhen Hai Zhang ◽  
Ke Jie Li ◽  
Hai Yan Shao ◽  
Tao Xu ◽  
...  
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
Real Time ◽  
Stationary State ◽  
Vision System ◽  
Image Rectification ◽  
Panoramic Vision ◽  
Panoramic Video ◽  
Environment Perception ◽  
Very High

Catadioptric panoramic vision system has been widely used in many fields, and also plays a very important role in environment perception of unmanned platform especially. However, the resolution of system is not very high, usually less than 5 million pixels at present. Even if the resolution is high, but the unwrapping and rectification of panoramic video is carried out off-line. Further, the system is also applied in stationary state or low stationary moving. This paper proposes an unwrapping and rectification method based on high-resolution catadioptric panoramic vision system used during non-stationary moving. It can segment dynamic circular mark region accurately and get the coordinates of center of circular image real-timely, shorten the time of image processing, meanwhile the coordinates of center and radius of the circular mark region would be obtained, so the image distortion caused by inaccurate center coordinates can be reduced. During image rectification, after achieving radial distortions parameters (K1, K2, K3), decentering distortions parameters (P1, P2), and the correction factor that has no physical meanings, we can used those for fitting the rectification polynomial, so the panoramic video can be rectified without distortion.

scholarly journals Diseño e implementación de un sistema de visión por computadora para el reconocimiento de objetos en movimiento

2019 ◽  
pp. 1-13
Author(s):  
Franco Javier Torres-Becerra ◽  
Miguel Angel Guzman-Altamirano ◽  
Jesús Hazael Garcia-Gallegoz ◽  
Javier Gustavo Cabal-Velarde
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Digital Filters ◽  
Vision System ◽  
Image Transformation ◽  
Computer Vision System ◽  
Geometric Figures ◽  
Web Camera ◽  
Controlled Environments ◽  
Black Color

In this work we developed a computer vision system that allow the geometric figures recognition in real time using a web camera, also the identification of the objects size using a known object. To make this possible we used several techniques of the digital image processing as gray scale filters because that’s the first step to start the image processing, threshold to make the image transformation in binary form where 1 is the white color and 0 the black color, edge detection to detect the edges of the figures therefore an important parameter is the noise cancelation of the obtained signals, that’s the reason of the using of digital filters because those allow the oscillation cancelation in the signals. The possible application can be the microorganism detection in controlled environments accord of its morphology also the change of its area in real time.

Sign in / Sign up

Export Citation Format

Share Document