• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.1-9
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• 2011

Recently, as mobile multimedia devices are used more and more, the needs for high-performance and low-energy multimedia processors are increasing. Application-specific integrated circuits (ASIC) can meet the needed high performance for mobile multimedia, but they provide limited, if any, generality needed for various application requirements. DSP based systems can used for various types of applications due to their generality, but they require higher cost and energy consumption as well as less performance than ASICs. To solve this problem, this paper proposes a single instruction multiple data (SIMD) based many-core processor which supports high-performance and low-power image data processing while keeping generality. The proposed SIMD based many-core processor composed of 16 processing elements (PEs) exploits large data parallelism inherent in image data processing. Experimental results indicate that the proposed SIMD-based many-core processor higher performance (22 times better), energy efficiency (7 times better), and area efficiency (3 times better) than conversional commercial high-performance processors.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.489-497
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• 1994

The most serious problems related to the cardiovascular prothesis are thrombosis and hemolysis. It is known that the flow pattern of cardiovascular prostheses is highly correlated with thrombosis and hemolysis. Laser Doppler Anemometry (LDA) is a usual method to get flow pattern, which is difficult to operate and has narrow measure region. Particle Image Velocimetry (PIV) can solve these problems. Because the flow speed of valve is too high to catch particles by CCD camera, high-speed camera (Hyspeed : Holland-Photonics) was used. The estimated maximum flow speed was 5m/sec and maximum trackable length is 0.5 cm, so the shutter speed was determined as 1000 frames per sec. Several image processing techniques (blurring, segmentation, morphology, etc) were used for the preprocessing. Particle tracking algorithm and 2-D interpolation technique which were necessary in making gridrized velocity pronto, were applied to this PIV program. By using Single-Pulse Multi-Frame particle tracking algorithm, some problems of PIV can be solved. To eliminate particles which penetrate the sheeted plane and to determine the direction of particle paths are these solving methods. 1-D relaxation fomula is modified to interpolate 2-D field. Parachute artificial heart valve which was developed by Seoul National University and Bjork-Shiely valve was testified. For each valve, different flow pattern, velocity profile, wall shear stress and mean velocity were obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1690-1710
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• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

• Journal of Digital Contents Society
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• v.14 no.1
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• pp.7-14
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• 2013

As mobiles devices with high-spec camera built in are used widely, the visual quality enhancement of the high-resolution images turns out to be one of the key capabilities of the mobile devices. Due to the limited computational resources of the mobile devices and the size of the high-resolution images, we should choose an image processing algorithm not too complex and use an efficient implementation technology. One of the simple and widely used image quality enhancement algorithms is contrast stretching. Java libraries running on a virtual machine, JNI (Java Native Interface) based native C/C++, and NEONTM SIMD (Single Instruction Multiple Data) are common implementation technologies in the case of Android smartphones. Using these three implementation technologies, we have implemented two image contrast stretching algorithms - linear and equalized, and compared the computation times. The native C/C++ and the NEONTM SIMD outperformed the native C/C++ implementation by 56-78 and 50-76 time faster respectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1139-1145
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• 2014

User recognition technology, which identifies or verifies a certain individual is absolutely essential under robotic environments for intelligent services. The conventional face recognition algorithm using single distance face image as training images has a problem that face recognition rate decreases as distance increases. The face recognition algorithm using face images by actual distance as training images shows good performance but this has a problem that it requires user cooperation. This paper proposes the LDA-based long distance face recognition method which uses multiple distance face images from a zoom camera for training face images. The proposed face recognition technique generated better performance by average 7.8% than the technique using the existing single distance face image as training. Compared with the technique that used face images by distance as training, the performance fell average 8.0%. However, the proposed method has a strength that it spends less time and requires less cooperation to users when taking face images.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.929-938
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• 2004

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with previously estimated pitch pose angle by the stereo geometry. Also, since we have an advantage that we can utilize two images acquired at the same time, we can increase overall recognition performance by decision-level fusion. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the yaw pose transform, and the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model. Also, by using stereo camera system we achieved an increased recognition rate 5.24% more for the case of upper face pose, and 3.34% more by decision-level fusion.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.17-25
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• 2019

In this paper, we introduce the technology to convert a single human image into a fashion show animation video clip. The technology can help the customers confirm the dynamic fitting result when combined with the virtual try on technique as well as the interesting experience to a normal person of being a fashion model. We developed an extended technique of full human 2D to 3D inverse modeling based on SMPLify human body inverse modeling technique, and a rigged model animation method. The 3D shape deformation of the full human from the body model was performed by 2 part deformation in the image domain and reconstruction using the estimated depth information. The quality of resultant animation videos are made to be publically available for evaluation. We consider it is a promising approach for commercial application when supplemented with the post - processing technology such as image segmentation technique, mapping technique and restoration technique of obscured area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.771-778
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• 2019

The traditional illuminance intensity detection method using a single sensor has a problem that uniformity of illuminance detection is deteriorated depending on the measurement position due to the narrow FOV characteristic. In order to overcome this problem, a method of detecting an average illuminance value through a plurality of illuminance sensors is used, but the complexity and detection error are increased. In this paper, we propose a illuminance intensity detection method based on a single image sensor with wide FOV. The proposed method can solve the problems such as system complexity and error increase of existing illuminance sensor. The test results show that the difference of average value is 12% using a illuminance sensor, 10.7% using five illuminance sensors, and 6.2% using an image sensor compared with the reference value using the color difference illuminometer. It is confirmed that the proposed method can easily and accurately detect the space illuminance with improved uniformity.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.257-264
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• 2019

This paper presents a single image haze removal method via a pixel-based joint BDCP (bright and dark channel prior) and a hierarchical bilateral filter in order to reduce computational complexity and memory requirement while improving the dehazing performance. Pixel-based joint BDCP reduces the computational complexity compared to the patch-based DCP, while making it possible to estimate the atmospheric light in pixel unit and the transmission more accurately. Moreover the bilateral filter, which can smooth an image effectively while preserving edges, refines the transmission to reduce the halo effects, and its hierarchical structure applied to edges only prevents the increase of complexity from the iterative application. Experimental results on various hazy images show that the proposed method exhibits excellent haze removal performance with low computational complexity compared to the conventional methods, and thus it can be applied in various fields.