ScholarWorks@Hanyang University ERICA Campus: Kim, Kibum

Detailed Information

Kim, Kibum (김기범)

COLLEGE OF COMPUTING (SCHOOL OF MEDIA, CULTURE, AND DESIGN TECHNOLOGY)

Research Area: 컴퓨터과학, 인간과컴퓨터상호작용, Computer Science, Human-Computer Interaction

Tel 031-400-1061
Homepage

ResearcherID ORCiD Scopus Google Scholar ID ResearchGate

Keyword

Virtual reality:4||Kary tree hashing:3||Body parts detection:3||Game:2||Logistic regression:2||Virtual reality (VR):2||Multilayer perceptron:2||Scene understanding:2||human action recognition:2||wayfinding:2||Input devices:2||Visualization:2||humanobject interaction:2||inertial sensors:2||people with visual impairment:2||Controller:2||pixel labeling:2||Neural network:2||3D point cloud:2||Kernel sliding perceptron:2||Texton forest segmentation:2||saliency map:2||Onair inputs:2||Feature extraction:2||fiducial points:2||semantic segmentation:2||maximum entropy Markov model:2||Gaussian mixture model:2||superpixels:2||geodesic distance:2||Image segmentation:2||VR:2||VR training system:2||Common Ground:1||Common ground:1||Compression ratio:1||Computer mediated communication:1||Contextaware features:1||Convolutional neural network:1||Crossline judgment:1||DIY:1||Daily life activity recognition  · Local binary pattern  · Mel frequency cepstral coeffi cients  · Optimization algorithm  · Reweighted genetic algorithm:1||Data gloves:1||Deep belief network:1||Deep belief networks:1||Deep learning method:1||Depth images:1||Depth sensors:1||Discrete Hartely Transform:1||Drag force:1||Effective compression ratio:1||Empirical investigations:1||Entropy:1||Entropy Markov model:1||Entropyscaled segmentation:1||Face detection:1||Face detectionlandmark analysisSVM classifierfacial expressions recognition:1||Fidelity:1||Full body silhouettes:1||Fused intrainter trajectories:1||GUI:1||Gait event classification:1||Games:1||Gaussian filter:1||Gaussian mapping:1||Hand Gesture:1||Hand gesture:1||Handhelds:1||Haptic:1||HeadMounted Device:1||Healthcare:1||Hough Circular Gradient Transform:1||Hough Voting:1||Human activity analysis:1||Human event recognition:1||Human interaction recognition:1||Human pose estimation:1||Human posture analysis:1||HumanComputer Interaction:1||Humancentered computing Interaction devices:1||Humancentered computingInteraction ParadigmsVirtual reality:1||Hybridfeatures:1||Image recognition:1||Inertial Measurement Unit (IMU):1||Inertial sensors:1||Jaccard similarity:1||KAry tree hashing classifier:1||Labeling:1||Landmark detection:1||Landmark localization:1||Large vertical display:1||LiDAR:1||MEP:1||Marking menus:1||Markov model:1||Medical conditions:1||Medical fitness:1||Mel frequency cepstral coefficients:1||Melfrequency cepstral coefficient:1||Mixed Reality:1||Modified maximum likelihood estimation sampling consensus:1||Motion gestures:1||Multi people tracking:1||Multiobject recognition:1||Multidimensional cues:1||Object detection:1||Object recognition:1||Object segmentation:1||Pediatrics:1||People with Visual Impairment:1||People with visual impairments:1||Physical activity monitoring:1||Physical activity recognition:1||Plane fitting:1||PointClouds:1||Posture estimation:1||Premixed charge compression ignition:1||Pressure:1||Probability Based Incremental Learning:1||Pseudo 2D stick model:1||Pulmonology:1||RGBD object recognition:1||RGBD object segmentation:1||RGBD sensors:1||Random sample consensus:1||Ray optimization:1||Restricted Boltzmann machines:1||Reweighted genetic algorithm:1||Scene recognition:1||Semantics:1||Sensor technologies:1||Sensors:1||Sequential Forward Selection:1||Serious Games:1||Showdown:1||Silhouette optimization:1||Skeleton joints:1||Skills:1||Skydiving:1||Spatiotemporal angulargeometric features:1||Spatiotemporal features:1||Sports activity recognition:1||Superpixels:1||Sustainable events classification:1||Sustainable object recognition:1||Sustainable physical healthcare pattern recognition:1||Synthetic model:1||Target selection:1||Template matching:1||Text entry:1||Threedimensional displays:1||Training:1||Unity3D:1||Unscented Kalman filter (UKF):1||Virtual Reality:1||Virtual Reality (VR):1||Virtual Realty:1||Visual attention:1||Visual communication:1||Visual impairment:1||Wearable sensors:1||Wearable sensors system:1||Wind velocity:1||academic performance:1||accelerometer and gyroscope sensors:1||accessibility:1||adaptive weighted median filter:1||affinitybased scheduling:1||artificial neural network:1||asthenia disease recognition:1||auditory (nonspeech) feedback:1||augmented reality:1||bag of features:1||binary grey wolf optimization:1||body parts detection:1||calibration:1||contextintelligence features:1||cross entropy:1||decision tree:1||deep learning:1||depth sensors:1||directional image:1||elderly/seniors:1||electrocardiogram:1||electrochemiluminescence:1||event detection:1||face detection:1||feature extraction and matching:1||feature reduction:1||fuzzy cmean segmentation:1||genetic algorithm:1||gestural input:1||gray wolf optimization:1||group cohesion:1||group efficacy:1||hand gesture recognition:1||haptic I/O:1||head tracking:1||healthcare monitoring:1||highperformance computing:1||human computer interaction:1||human locomotion:1||interaction paradigms:1||interaction style:1||landmark localization:1||linear discriminant analysis:1||load balancing:1||logistic regression:1||machine learning:1||marking gestures:1||maximum entropy:1||medical information systems:1||medical treatment:1||multifused features:1||multiobject detection:1||multilevel analysis:1||multiple kernel learning:1||multiple objects categorization:1||nanomaterials:1||neurofuzzy classifier:1||object pattern:1||object segmentation:1||overground walking:1||parallel computing:1||particle swarm optimization:1||pen computing:1||people counting:1||people tracking:1||pesticide contaminants:1||point cloud:1||pointing:1||projection mapping:1||recognition:1||reweighted genetic algorithm:1||scene classification:1||scene detection:1||selforganized map:1||spatial memory:1||statistical segmentation:1||surveillance:1||sustainable surveillance system:1||tables and interactive surfaces:1||teambuilding:1||training:1||trajectory features:1||virtual reality:1||virtual worlds:1||visual attention:1||visual sensors:1||visually impaired people:1||walkinplace:1||wearable sensors:1||가상현실:1||게임 경험:1||게임 컨트롤러:1||능동적:1||닌텐도 라보(Nintendo LABO):1||닌텐도 스위치(Nintendo Switch):1||라보(Labo):1||마이크로비트:1||바이저:1||반려동물:1||사고력:1||아트킨슨 사이클:1||압축비:1||예혼합 압축착화:1||유대감:1||유효압축비:1||인터렉션 디자인:1||평균유효 압력:1||학습용 게임:1||0180 degree intensity features:1||헬스케어:1||1D Haar Wavelet transform:1||2D stick model:1||2D to 3D reconstruction:1||3D motion:1||Accelerometer:1||Accessibility:1||Active Shape Model:1||Activity detection system:1||Activity recognition · Depth silhouettes · Feature extraction · Smart home:1||Adaboost:1||Adam optimization:1||Air gesture:1||Anthropometric model:1||AprioriAssociation:1||Arduino:1||Artificial neural network:1||Assistive Technology:1||Assistive technology:1||Atkinson cycle:1||Bag of features:1||Bayesian generative model:1||Behavioral sciences:1||Biological system modeling:1||Biomedical measurement:1||Biomedical monitoring:1||Biosensing:1||Blind:1||Body sensors · Human motion detection · Regression trees · Smart home:1||CSCL (computer supported collaborative learning):1||CSCW (computer supported cooperative work):1||Cardboard:1||Collaboration:1||

STATISTICS: Total View :2,269,148; Today View :1,420

RSS_1.0 RSS_2.0 ATOM_1.0

55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269

Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.

Detailed Information

Keyword

BROWSE