scholarly journals Development of Adaptive Image Processing based on FPGA for Real-time Robot Vision System

2013 ◽  
Author(s):  
Hayato Hagiwara ◽  
Kenichi Asami ◽  
Mochimitsu Komori
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Vision System ◽  
Robot Vision ◽  
Adaptive Image Processing

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.

Robot Vision System for Human Detection and Action Recognition

2020 ◽  
Vol 24 (3) ◽  
pp. 346-356
Author(s):  
Satoshi Hoshino ◽  
◽  
Kyohei Niimura
Keyword(s):  
Optical Flow ◽  
Real Time ◽  
Action Recognition ◽  
Autonomous Navigation ◽  
Vision System ◽  
Robot Vision ◽  
Human Detection ◽  
Time Performance ◽  
Camera Sensors ◽  
Camera Sensor

Mobile robots equipped with camera sensors are required to perceive humans and their actions for safe autonomous navigation. For simultaneous human detection and action recognition, the real-time performance of the robot vision is an important issue. In this paper, we propose a robot vision system in which original images captured by a camera sensor are described by the optical flow. These images are then used as inputs for the human and action classifications. For the image inputs, two classifiers based on convolutional neural networks are developed. Moreover, we describe a novel detector (a local search window) for clipping partial images around the target human from the original image. Since the camera sensor moves together with the robot, the camera movement has an influence on the calculation of optical flow in the image, which we address by further modifying the optical flow for changes caused by the camera movement. Through the experiments, we show that the robot vision system can detect humans and recognize the action in real time. Furthermore, we show that a moving robot can achieve human detection and action recognition by modifying the optical flow.

A Novel Robot Vision Employing a Silicon Retina

2001 ◽  
Vol 13 (6) ◽  
pp. 614-620 ◽  
Author(s):  
Kazuhiro Shimonomura ◽  
◽  
Seiji Kameda ◽  
Kazuo Ishii ◽  
Tetsuya Yagi ◽  
...  
Keyword(s):  
Real Time ◽  
Integrated Circuit ◽  
Large Scale ◽  
Analog Circuit ◽  
Vision System ◽  
Robot Vision ◽  
Illumination Condition ◽  
Output Image ◽  
Analog Cmos ◽  
Silicon Retina

A Robot vision system was designed using a silicon retina, which has been developed to mimick the parallel circuit structure of the vertebrate retina. The silicon retina used here is an analog CMOS very large-scale integrated circuit, which executes Laplacian-Gaussian like filtering on the image in real time. The processing is robust to change of illumination condition. Analog circuit modules were designed to detect the contour from the output image of the silicon retina and to binarize the output image. The images processed by the silicon retina as well as those by the analog circuit modules are received by the DOS/V-compatible mother-board with NTSC signal, which enables higher level processings using digital image processing techniques. This novel robot vision system can achieve real time and robust processings in natural illumination condition with a compact hardware and a low power consumption.

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