In this paper, we propose a new image alignment technique based on CUDA SURF in order to solve the initial image alignment problem that frequently occurs in machine vision applications. Machine vision systems using multi-spectral images have recently become more common for solving various decision problems that cannot be performed by the human vision system. These machine vision systems mostly use markers for the initial image alignment. However, there are some applications where the markers cannot be used and the alignment techniques have to be changed whenever their markers are changed. In order to solve these problems, we propose a new image alignment method for multi-spectral machine vision applications based on SURF extracting image features without depending on markers. In this paper, we propose an image alignment method that obtains a sufficient number of feature points from multi-spectral images using SURF and removes outlier iteratively based on a least squares method. We further propose an effective preliminary scheme for removing mismatched feature point pairs that may affect the overall performance of the alignment. In addition, we reduce the execution time by implementing the proposed method using CUDA based on GPGPU in order to guarantee real-time operation. Simulation results show that the proposed method is able to align images effectively in applications where markers cannot be used.

Non-photo realistic Rendering is the one of the fields in Computer Graphics and many painterly rendering techniques have been studying. However studies about a specific painter are still in a rarity. Therefore in this paper, we studied about technique for generation of Henri de Toulouse-Lautrec's portraits. Toulouse-Lautrec was a painter in 19th century. His style of portraits was expressed as follows; the sketch was drawn by conte or pastel in croquis style and colored only focused parts like faces on the base colored area. For simulate this, we propose sequential technique about sketch style image generation and face area painting.

In this paper, we propose a novel approach to improve the performance of a voice activity detection(VAD) which is based on the adaptive band-partitioning with the likelihood ratio(LR). The previous method based on the adaptive band-partitioning use the weights that are derived from the variance of the spectral. In our VAD algorithm, the weights are derived from LR, and then the weights are incorporated with the entropy. The proposed algorithm discriminates the voice activity by comparing the weighted entropy with the adaptive threshold. Experimental results show that the proposed algorithm yields better results compared to the conventional VAD algorithms. Especially, the proposed algorithm shows superior improvement in non-stationary noise environments.

Due to a number of illegal copied videos, many video content markets have been threatened. Since this copied videos have intercepted the profits of the content holders, content developers lose the will to generate new contents. Therefore, video copy detection approaches have been developed to protect the copyrights of video contents. However, many illegal uploader who generate copied videos used video transformations to avoid video copy detection systems. Among of the video transformations, rotation and flipping did not distorted the quality of video contents. Thus, these two video transformations were adopt to generate copied video. In order to detect rotated or flipping copy videos, rotation and flipping robust region binary pattern (RFR) recently was proposed. But, this RFR has a weakness according to rotated angles. Therefore, in order to overcome this problem, multi region binary patterns are proposed in this paper. The proposed method has the similar performance with the original RFR. But, it showed much higher efficiency for memory spaces.

We propose an emotional facial avatar that portrays the user's facial expressions with an emotional emphasis, while achieving visual and behavioral realism. This is achieved by unifying automatic analysis of facial expressions and animation of realistic 3D faces with details such as facial hair and hairstyles. To augment facial appearance according to the user's emotions, we use emotional templates representing typical emotions in an artistic way, which can be easily combined with the skin texture of the 3D face at runtime. Hence, our interface gives the user vision-based control over facial animation of the emotional avatar, easily changing its moods.

When demand for transmitting multimedia data increases, network congestion is more likely to occur and users will suffer high loss rate as well as high delay. In order to enhance quality-of-service (QoS) of video multicasting, we need to raise transmission reliability and reduce end-to-end delay. This paper proposes a routing mechanism for a OpenFlow-based small-scale network in order to multicast video reliably with low delay. In our method, multipath routing will be applied to Multiple Description (MD) Coded video to exploit its multi-description property. Through performance evaluation, our method shows improvement on loss rate, delay and video distortion.

It is difficult to perform automatic formation flight of UAV (Unmanned Aerial vehicle) when GPS (Global Positionig System) is out of order or has a system error, since the relative position estimation in the flight group is impossible in that case. In this paper, we design a relative localization system for the automatic formation flight of UAV. For this purpose, we adopt digital beam forming (DBF) to estimate the angle with the central controller of the flight group and Particle Filtering scheme to compensate the estimation error of ToA (time of arrival) method. Computer simulation results present a proper distance between the central controller and a following unit to maintain the automatic formation flight.

Smartphone is very much ingrained into our lives and it has propagated rapidly. With the growing expansion of smartphone, the number of lost smartphones has proliferated all the while. Unlike common personal belongings, smartphone is a high-priced goods and has personal information. In case it gets lost or stolen, it will cause monetary damage as well as secondary damage of personal information leaks. To lesson the damage, diverse applications that prevent the loss of a smartphone have been developed. But existing applications place emphasis on providing countermeasures that tracks the missing smartphones. Therefore, this paper describes the design and implementation of a smartphone application which provides precautionary functions to prevent the loss of a smartphone and countermeasures to track the missing smartphone. The implemented application prevents the loss of a smartphone using satefy zone and movement detection. In the event we lose a smartphone, it helps us recover a lost property using location tracking and remote control functions quickly and efficiently.

In large-scale crowd simulations, it is very important for the decision-making system of manipulating interactive behaviors to minimize the computational cost for controlling realistic behaviors such as collision avoidance. In this paper, we propose a large-scale realtime crowd simulation method using the affordance and navigation potential fields such as attractive and repulsive forces of electromagnetic fields. In particular, the model that we propose locally handles the realistic interactions between agents, and thus radically reduces the cost of expensive computation on interactions which has been the most problematic in crowd simulation. Our method is widely applicable to the expression and analysis of various crowd behaviors that are needed in behavior control in computer games, crowd scenes in movies, emergent behaviors of evacuation, etc.

The objective of this study is to present a new design method at the idea brainstorming process, which requires a great deal of time and effort to seek their own ideas in existing design process and to develop a user support idea forms generation system called OCIGS (Openware Creative Idea Generation System) that makes it possible to create a variety and 3D forms as well as a quantitative evaluation data for the actual types that compose the aesthetic factors and designs of qualitative standards. In order to achieve these objectives : First, overcoming the limitation of 3D form generation ability by establishing visual application system, Second, accepting users' opinions by generating 3D images dynamically, analysing and giving information on the preferred ones on the web on real time, Third, identifying tendency of preference so that they can generate preferred colors and images in future by updating image combination and dropping low-preferred ones. This system would play a role as an idea or form generation application in the actual 3d form design development process.

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

The history of mankind has been together with the history of image because image provides with excellent information as a communication means. However, this study argues that there is more underlying cause for it. A subject is the subject of unconscious and the role of image is huge in the process toward the subject. Of course, image has been dealt in-depth in psychoanalysis. Film study also applied psychoanalysis on it. However, they were not the approach from the viewpoint with image in the center. Accordingly, this study will verify the image toward the subject and the absoluteness of image. The result of this study is that image intervened deeply in the formation of the subject much higher than the level of simple communication. Since image communicates with the subject on more underlying level, the subject have been always entangled with image and men have delved in image and been attracted to it.