Character attachment in team-based first person shooter game with respect to the role in the combat among Korean young gamers

Character attachment have been studied thoroughly from the view of psychology and media researches. In game playing, the player-avatar relationship is a form of character attachment and affects a good game design as well as management systems such as character customizing and in game purchasing policy. In this paper, we investigate such player-avatar relationship on the theme of team-based FPS where in general the attachment is not expected to be high. However, from the online survey for Tom Clancy’s Rainbow 6 Siege mania groups, we find that there are different character attachment patterns with respect to the role of players in the team–attacker, defender, and supporter. It shows that attackers think avatar as an ‘object, but the defenders show more ‘avatar as others’ than the attackers. The supporters show high responsibility for the avatar and their play style is most like ‘avatar as symbiote’ manner

Fully automatic segmentation of intima/adventitia of the vessel using Bezier curve from intravascular ultrasound

Although medical image segmentation field is regarded as one of most established fields, still fully automatic segmentation to extract target object with high accuracy from intravascular ultrasound (IVUS) is very active area of research. In this paper, we propose a fully automatic morphological approach using Bezier curve in interpolating the boundaries of intima/adventitia of the vessel from IVUS with careful binarization algorithms. In experiment with 800 IVUS images, the proposed method is as good as fuzzy C-means based approach in comparison with human expert’s result with 84.4% satisfaction and better than other morphological method in all performance indices of curve fitting with 97.02% in accuracy and 58.19% in precision

Intelligent Automatic Extraction of Canine Cataract Object with Dynamic Controlled Fuzzy C-Means based Quantization

Canine cataract is developed with aging and can cause the blindness or surgical treatment if not treated timely. Since the pet owner do not have professional knowledge nor professional equipment, there is a growing need of providing pre-diagnosis software that can extract cataract-suspicious regions from simple photographs taken by cellular phones for the sake of preventive public health. In this paper, we propose a software that is highly successful for that purpose. The proposed software uses dynamic control of FCM clusters in quantification and trapezoid membership function in fuzzy stretching in order to enhance the intensity contrast from such rough photograph input. Through experiment, the proposed system demonstrates sufficiently enough accuracy in extraction (successful in 42 out of 45 cases) with better quality comparing with previous attempt

Developing an automatic brachial artery segmentation and bloodstream analysis tool using possibilistic C-means clustering from color doppler ultrasound images

Automatic segmentation of brachial artery and blood-flow dynamics are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose a software that is noise tolerant and fully automatic in segmentation of brachial artery from color Doppler ultrasound images. Possibilistic C-Means clustering algorithm is applied to make the automatic segmentation. We use HSV color model to enhance the contrast of bloodstream area in the input image. Our software also provides index of hemoglobin distribution with respect to the blood flow velocity for pathologists to proceed further analysis. In experiment, the proposed method successfully extracts the target area in 59 out of 60 cases (98.3%) with field expert’s verification

Effective Computer-Assisted Automatic Cervical Vertebrae Extraction with Rehabilitative Ultrasound Imaging by using K-means Clustering

Neck pain is one of most common musculoskeletal condition resulting in significant clinical, social and economic costs. Muscles around cervical spine including deep neck flexors play a key role to support and control its stability, thus monitoring such muscles near cervical vertebrae is important. In this paper, we propose a fully automated computer assisted method to detect cervical vertebrae with K-means pixel clustering from ultrasonography. The method also applies a series of image processing algorithms to remove unnecessary organs and noises in the process. The experiment verifies that our approach is consistent with human medical experts’ decision to locate key measuring point for muscle analysis and successful in detecting cervical vertebrae accurately – successful in 48 out of 50 test cases (96%)

Vision-based Crack Identification on the Concrete Slab Surface using Fuzzy Reasoning Rules and Self-Organizing

Identifying cracks on the surface of concrete slab structure is important for structure stability maintenance. In order to avoid subjective visual inspection, it is necessary to develop an automated identification and measuring system by vision based method. Although there have been some intelligent computerized inspection methods, they are sensitive to noise due to the brightness contrast and objects such as forms and joints of certain size often falsely classified as cracks. In this paper, we propose a new fuzzy logic based image processing method that extracts cracks from concrete slab structure including small cracks that were often neglected as noise. We extract candidate crack areas by applying fuzzy method with three color channel values of concrete slab structure. Then further refinement processes are performed with Self Organizing Map algorithm and density based noise removal process to obtain basic crack characteristic attributes for further analysis. Experimental result verifies that the proposed method is sufficiently identified cracks with various sizes with high accuracy (97.3%) among 1319 ground truth cracks from 30 images

Automatic segmentation of large bowl obstruction area with hough transform from erect abdominal radiograph images

Large bowel obstruction is less frewuent but often appears acute and needs emergent treatment. Erect abdominal radiograph is usually the first imaging study performed in patients suspected of having large bowel obstruction. However, that mordality suffers from operator subjectivity thus a fully automatic computer aied tool is necessary. In this paper, we peopose an automatic large bowel feature (air-fluid region) segmentation method based on Canny edge detection and Hough transform. In experiment, the proposed method was successful in finding target region from large bowel obstruction patients’ radiographic images in all 30 cases provided. Whilie limited only applicable to the large bowel obstruction cases, the proposed method is practically feasible in application

Analysis and evaluation of mobile rhythm games : Game structure and playability

The rhythm game is an action simulation game adapted to the presented music. While it is expected to have an educational effect as a functional game, the relationship between the operability and rhythm education under the mobile platform is still questionable. In Korea, it seems that mobile rhythm game is a minority maniac genre that are played mostly among teenagers and early twenties. In this paper, we select three mobile rhythm games that are most played by Korean gamers in analysis. First, we analyze the user interface layout, note control, evaluation style and level of difficulty for three games – Deeno, Cytus, and Lanota. Then, we take a user survey in order to evaluate the playability of those games. All three games obtain high scores but there exust several statistically significant differences among games in analysis

Gender inequality among champions and players’ reception of gender disproportion of utility support champions in league of legends

Designing female character in video game has been criticized as being sexually objectified and underrepresented in quantity (number of characters and their appearance rate in the game) and in quality (take only secondary role and inferior ability statistics given). In this paper, we analyze world leading multiple-user online battle arena game league of legends to see if previously criticized gender inequality of champions still stands and conduct a survey of 1,403 players of that game and asks how they feel about serious gender disproportion of utility support champions (all females). The result shows that league of legends still has serious gender disparity in performance parameters and there has been only a small change in 5-year span (2014-2019). The survey result tells us that game players also feel political incorrectness of such gender disproportion, but they accept such gender prototype because they have been taught as such as social role theory explains gender inequality issues

Automatic segmentation of wrist bone fracture area by K-means pixel clustering from X-ray image

Early detection of subtle fracture is important particularly for the senior citizens’ quality of life. Naked eye examination from X-ray image may cause false negatives due to operator subjectivity thus computer vision based automatic detection software is much needed in practice.  In this paper, we propose an automatic extraction method for suspisious wrist fracture regions. We apply K-means in pixel clustering to form the candidate part of possible fracture from wrist X-ray image automatically. This method can recover previously detected patterned false cases with edge detection method after fuzzy stretching. The proposed method is successful in 16 out of 20 tested cases in experiment