• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1183-1188
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• 2016

Kinect sensor version 2 is a kind of camera released by Microsoft as a computer vision and a natural user interface for game consoles like Xbox one. It allows acquiring color images, depth images, audio input and skeletal data with a high frame rate. In this paper, using depth image, we present a surveillance system of a certain area within Kinect's field of view. With computer vision library(Emgu CV), if an object is detected in the target area, it is tracked and kinect camera takes RGB image to send it in database server. Therefore, a mobile application on android platform was developed in order to notify the user that Kinect has sensed strange motion in the target region and display the RGB image of the scene. User gets the notification in real-time to react in the best way in the case of valuable things in monitored area or other cases related to a reserved zone.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.24-29
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• 2014

This paper proposes a kinect-based human motion recognition model for the 3D contents control after tracking the human body gesture through the camera in the infrared kinect project. The proposed human motion model in this paper computes the distance variation of the body movement from shoulder to right and left hand, wrist, arm, and elbow. The human motion model is classified into the movement directions such as the left movement, right movement, up, down, enlargement, downsizing. and selection. The proposed kinect-based human motion recognition model is very natural and low cost compared to other contact type gesture recognition technologies and device based gesture technologies with the expensive hardware system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.818-819
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• 2014

Recently there are many works conducted on utilizing the DIBR (Depth-Image-Based Rendering) based intermediate images for the three-dimensional displays that do not require the use of stereoscopic glasses. However the prior works have used expensive depth cameras to obtain high-resolution depth images since DIBR-based intermediate image generation method requires the accuracy for depth information. In this study, we have developed the simulation to generate multi-view intermediate images based on the depth and color images using Microsoft Kinect. This simulation aims to support the acquisition of multi-view intermediate images utilizing the low-resolution depth and color image from Kinect, and provides the integrated service for the quality evaluation of the intermediate images. This paper describes the architecture and the system implementation of this simulation program.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.447-458
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• 2012

We present a method to recognize hand gestures using skeletal joint data obtained from Microsoft's Kinect sensor. We propose a combination feature of multi-angle histograms robust to orientation variations to represent the observation sequence of skeletons. The proposed feature efficiently represents the orientation variations of gestures that can be occurred according to person or environment by combining the multiple angle histograms with various angular-quantization levels. The gesture represented as combination of multi-angle histograms and random decision forest classifier improve the recognition performance. We conduct the experiments in hand gesture dataset obtained from a kinect sensor and show that our method outperforms the other methods by comparing the recognition performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.403-411
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• 2022

A motion-based sports game uses a motion sensor or a camera to exercise based on body movements, and it is possible to obtain exercise effects such as improving physical strength while enjoying the game. In prior works, various studies such as usability evaluation has been conducted on motion-based sports games. However, there has been no discussion about how the exercise effect is exerted on users when experiencing motion-based sports games as individual or team play. This study compared the user's exercise effects by analyzing the user's ECG (Electrocardiogram) sensor and the Kinect sensor's skeletal information using Nintendo Switch game that is played individually and as a team. In this paper, the experimental design and method, the quantitative measurement results based on ECG and Kinect, and the results of the post-test subjective measurement are discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.179-185
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• 2014

In this paper, a quadruped walking pet robot for human-robot interaction, a robot-controller using a smart phone application program, and a home smart control system using sensor informations providing from the robot are described. The robot has 20 degree of freedom and consists of various sensors such as Kinect sensor, infrared sensor, 3 axis motion sensor, temperature/humidity sensor, gas sensor and graphic LCD module. We propose algorithms for the robot entertainment: walking algorithm of the robot, motion and voice recognition algorithm using Kinect sensor. emotional expression algorithm, smart phone application algorithm for a remote control of the robot, and home smart control algorithm for controlling home appliances. The experiments of this paper show that the proposed algorithms applied to the pet robot, smart phone, and computer are well operated.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.1-10
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• 2018

Aggression among pigs adversely affects economic returns and animal welfare in intensive pigsties. Recently, some studies have applied information technology to a livestock management system to minimize the damage resulting from such anomalies. Nonetheless, detecting each pig in a crowed pigsty is still challenging problem. In this paper, we propose a new Kinect camera and deep learning-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The standing-pigs are detected by using YOLO (You Only Look Once) which is the fastest and most accurate model in deep learning algorithms. Our experimental results show that this method is effective for detecting individual pigs in real time in terms of both cost-effectiveness (using a low-cost Kinect depth sensor) and accuracy (average 99.40% detection accuracies).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.275-276
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• 2016

In this paper, we were implemented the application to induce correct posture by recognizing the incorrect posture of the user. Implemented system uses kinect sensors to determine the user's position information, it has been developed posture determination algorithm that can determine the four wrong posture and correct posture. In addition to PC in order to improve the user convenience and accessibility, to implement real-time monitoring application that can determine the user's position in the smartphone. For the system of performance evaluation of and promote the attitude determination experiment to target the five college students, the experimental results sensitivity and specificity of it it was found that the attitude determination performance is excellent at 0.956.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1106-1112
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• 2013

Microsoft released motion sensing device named Kinnect on early 2010, which is available for developing Xbox 360 game and entertainment software. Also many third party libraries and applications are developed for Kinnect. In this paper, we studied and developed guitar rhythm game on Kinnect using three sensor units on it. Rhythm game is the most popular game genre for many game devices including PC, console device, and smart phone. The main reasons for their popularity depends on their simplicity, short learning time and physical activity with rhythms. We developed the game screen and layout on DirectX 11, also we used OpenNI library for recognize physical activity of gamer's body and fingers, and OpenGL for body gestures on the game.