• ETRI Journal
• /
• v.33 no.2
• /
• pp.251-258
• /
• 2011

Applying face alignment after face detection exerts a heavy influence on face recognition. Many researchers have recently investigated face alignment using databases collected from images taken at close distances and with low magnification. However, in the cases of home-service robots, captured images generally are of low resolution and low quality. Therefore, previous face alignment research, such as eye detection, is not appropriate for robot environments. The main purpose of this paper is to provide a new and effective approach in the alignment of small and blurred faces. We propose a face alignment method using the confidence value of Real-AdaBoost with a modified census transform feature. We also evaluate the face recognition system to compare the proposed face alignment module with those of other systems. Experimental results show that the proposed method has a high recognition rate, higher than face alignment methods using a manually-marked eye position.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.5
• /
• pp.496-504
• /
• 2009

This paper presents a recognition performance of VOR (Vestibular-Ocular Reflex) based vision tracking system for mobile robot. The VOR is a reflex eye movement which, during head movements, produces an eye movement in the direction opposite to the head movement, thus maintaining the image of interested objects placed on the center of retina. We applied this physiological concept to the vision tracking system for high recognition performance in mobile environments. The proposed method was implemented in a vision tracking system consisting of a motion sensor module and an actuation module with vision sensor. We tested the developed system on an x/y stage and a rate table for linear motion and angular motion, respectively. The experimental results show that the recognition rates of the VOR-based method are three times more than non-VOR conventional vision system, which is mainly due to the fact that VOR-based vision tracking system has the line of sight of vision system to be fixed to the object, eventually reducing the blurring effect of images under the dynamic environment. It suggests that the VOR concept proposed in this paper can be applied efficiently to the vision tracking system for mobile robot.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.196-199
• /
• 2010

The human eyes are important facial landmarks for image normalization due to their relatively constant interocular distance. This paper introduces a novel approach for the eye detection task using optimal segmentation method for eye representation. The method consists of three steps: (1)edge extraction method that can be used to accurately extract eye region from the gray-scale face image, (2)extraction of eye region using labeling method, (3)eye localization based on intensity information. Experimental results show that a correct eye detection rate of 98.9% can be achieved on 2408 FERET images with variations in lighting condition and facial expressions.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.4
• /
• pp.97-103
• /
• 2008

This study is to present a fainting motion recognizing method by using fish-eye lens images to sense emergency situations. The camera with fish-eye lens located at the center of the ceiling of the living room sends images, and then the foreground pixels are extracted by means of the adaptive background modeling method based on the Gaussian complex model, which is followed by tracing of outer points in the foreground pixel area and the elliptical mapping. During the elliptical tracing, the fish-eye lens images are converted to fluoroscope images. the size and location changes, and moving speed information are extracted to judge whether the movement, pause, and motion are similar to fainting motion. The results show that compared to using fish-eye lens image, extraction of the size and location changes. and moving speed by means of the conversed fluoroscope images has good recognition rates.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.7
• /
• pp.75-81
• /
• 2010

In this paper, we propose an emotion messenger which recognizes face or hand gestures of a user using a WebCAM, converts recognized emotions (joy, anger, grief, happiness) to flash-cones, and transmits them to the counterpart. This messenger consists of face recognition module, hand gesture recognition module, and messenger module. In the face recognition module, it converts each region of the eye and the mouth to a binary image and recognizes wink, kiss, and yawn according to shape change of the eye and the mouth. In hand gesture recognition module, it recognizes gawi-bawi-bo according to the number of fingers it has recognized. In messenger module, it converts wink, kiss, and yawn recognized by the face recognition module and gawi-bawi-bo recognized by the hand gesture recognition module to flash-cones and transmits them to the counterpart. Through simulation, we confirmed that CPU share ratio of the emotion messenger is minimized. Moreover, with respect to recognition ratio, we show that the hand gesture recognition module performs better than the face recognition module.

• The Journal of the Korea Contents Association
• /
• v.13 no.1
• /
• pp.1-8
• /
• 2013

The accuracy of a real facial recognition system can be varied according to the accuracy of the eye detection algorithm when we design and implement a semi-automatic facial recognition algorithm depending on the eye position of a database. In this paper, a fully automatic facial recognition algorithm is proposed such that Gabor and LBP features are extracted from fiducial points of a face graph which was created by using fiducial points based on the eyes, nose, mouth and border lines of a face, fitted on the face image. In this algorithm, the recognition performance could be increased because a face graph can be fitted on a face image automatically and fiducial points based LPB features are implemented with the basic Gabor features. The simulation results show that the proposed algorithm can be used in real-time recognition for more than 1,000 faces and produce good recognition performance for each data set.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.9
• /
• pp.1269-1278
• /
• 2002

The more high growth of knowledge, the more need personal identity technique. Fingerprint or iris of the eye identity techniques are already commercialized and used various field. Using human face recognition or authentication are not high performance yet. But application for an organism or face recognition are expected getting important. We propose a user recognition system by verifying similarity comparison of eye and lip component images which are splitted, calculated characteristic rate of each facial components and added weight to special formula. Through test proposed methods and analysis the result, we got a high recognition rate.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.120-121
• /
• 2006

In this paper, We have designed a face recognition system based on the embedded Linux. This paper has an aim in embedded system to recognize the face more exactly. At first, the contrast of the face image is adjusted with lightening compensation method, the skin and lip color is founded based on YCbCr values from the compensated image. To take advantage of the method based on feature and appearance, these methods are applied to the eyes which has the most highly recognition rate of all the part of the human face. For eyes detecting, which is the most important component of the face recognition, we calculate the horizontal gradient of the face image and the maximum value. This part of the face is resized for fitting the eye image. The image, which is resized for fit to the eye image stored to be compared, is extracted to be the feature vectors using the continuous wavelet transform and these vectors are decided to be whether the same person or not with PNN, to miminize the error rate, the accuracy is analyzed due to the rotation or movement of the face. Also last part of this paper we represent many cases to prove the algorithm contains the feature vector extraction and accuracy of the comparison method.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.12 no.2
• /
• pp.150-161
• /
• 2012

Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ms in a VGA image.

• (The) Korean Journal of Advertising
• /
• v.29 no.7
• /
• pp.29-53
• /
• 2018

In our study, we investigated the effects of position of endorser and endorser's gaze direction(direct/averted_image/averted_text) on advertising attitude, purchase intent and brand recognition using eye-tracking method. Focusing on the printed cosmetic ads which the role of endorser is important and indirect persuade route is relatively is emphasized, we conducted experiment on 36 participants in 20s. As prior studies, our results shows that participants paid attention to more and faster on specific element which the endorser is gazing at. But it was not reflected to ad attitude and purchase intent directly. When the endorser is positioned in left the side, the highest purchase intent was shown in direct gaze condition, while when the endorser is on the right side, the highest ad attitude was shown in gazing image condition. Additionally, the brand recognition task following eye-tracking experiment shows that recognition accuracy was higher only in condition which the endorser is in the left side looking at the product image. These results demonstrated that the gaze direction of endorser plays a role as attentional guidance, which means it can lead customer's attention to particular region in the printed ad, but the effect can be varied depending on the position of endorser and which type of information the endorser is gazing at. Therefore, ultimately, to increase customer's ad attitude and purchase intent, complex consideration of not only the gazing direction of the endorser, but the position of endorser and other diverse elements is necessary.