• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.379-383
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• 2015

This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.616-617
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• 2013

This paper introduces a new method that controls a humanoid robot detecting a human motion using a Kinect sensor. Processing the output of a depth seneor of the Kinect sensor, we build a human stick model which represents each joint of human body. We detect a specific motion by calculating the distance and angle between joints. We send the control message to the robot using Bluetooth wireless communication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.625-626
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• 2013

This paper introduces a new method that detects human motions using a Kinect sensor. Also this paper describes a method to mimic the detected human motions. We first build a human stick model by processing the output of Kinect sensor. We detect a specific motion by using the position of each joint of the human stick model and by using the angles between joints.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.73-80
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• 2017

In this paper, we design and implement a mobile game based on Kinect sensor. This game is a motion recognition maze game based on Kinect sensor using XNA Game Studio. The game consists of three stages. Each maze has different size and clear time limit. A player can move to the next stage only if the player finds the exit within a limited time. However, if the exit is not found within the time limit, the game ends. In addition, two kinds of mini games are included in the game. The first game is a fruit catch game using motion recognition tracking of the Kinect sensor, and player have to pick up a certain number of randomly falling fruits. If a player acquire a certain number of fruits at this time, the movement speed of the player is increased. However, if a player takes a skeleton that appears randomly, the movement speed will decrease. The second game is a Quiz game using the speech recognition function of the Kinect sensor, and a question from random genres of common sense, nonsense, ancient creature, capital, constellation, etc. are issued. If a player correctly answers more than 7 of 10 questions, the player gets useful items to use in finding the maze. This item is a navigator fairy that helps the player to escape the forest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.205-213
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• 2018

Development and validation of crop models often require measurements of biomass for the crop of interest. Considerable efforts would be needed to obtain a reasonable amount of biomass data because the destructive sampling of a given crop is usually used. The Kinect sensor, which has a combination of image and depth sensors, can be used for estimating crop biomass without using destructive sampling approach. This approach could provide more data sets for model development and validation. The objective of this study was to examine the applicability of the Kinect sensor for estimation of chinese cabbage fresh weight. The fresh weight of five chinese cabbage was measured and compared with estimates using the Kinect sensor. The estimates were obtained by scanning individual chinese cabbage to create point cloud, removing noise, and building a three dimensional model with a set of free software. It was found that the 3D model created using the Kinect sensor explained about 98.7% of variation in fresh weight of chinese cabbage. Furthermore, the correlation coefficient between estimates and measurements were highly significant, which suggested that the Kinect sensor would be applicable to estimation of fresh weight for chinese cabbage. Our results demonstrated that a depth sensor allows for a non-destructive sampling approach, which enables to collect observation data for crop fresh weight over time. This would help development and validation of a crop model using a large number of reliable data sets, which merits further studies on application of various depth sensors to crop dry weight measurements.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.593-605
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• 2022

The purpose of this study is to investigate the personalized treacmill exercise analysis using a smart mirror based on Kinect sensor. To evaluate the performance of the development system, 10 health males were used to measure the range of the hip joint, knee joint, and ankle joint using a smart mirror when walking on a treadmill. For the validity and reliability of the development system, the validity and reliability were analyzed by comparing the human movement data measured by the Kinect sensor with the human movement data measured by the infrared motion capture device. As a result of validity verification, the correlation coefficient r=0.871~0.919 showed a high positive correlation, and through linear regression analysis, the validity of the smart mirror system was 88%. Reliability verification was conducted by ICC analysis. As a result of reliability verification, the correlation coefficient r=0.743~0.916 showed high correlation between subjects, and the consistency for repeated measurement was also very high at ICC=0.937. In conclusion, despite the disadvantage that Kinect sensor is less accurate than the motion capture system, Kinect is it has the advantage of low price and real-time information feedback. This means that the Kinect sensor is likely to be used as a tool for evaluating exercise prescription through human motion measurement and analysis.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.189-194
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• 2016

Recently, there is increasing demand for image processing technology while activated the use of equipments such as camera, camcorder and CCTV. In particular, research and development related to 3D image technology using the depth camera such as Kinect sensor has been more activated. Kinect sensor is a high-performance camera that can acquire a 3D human skeleton structure via a RGB, skeleton and depth image in real-time frame-by-frame. In this paper, we develop a system. This system captures the motion of a 3D human skeleton structure using the Kinect sensor. And this system can be stored by selecting the motion file format as trc and bvh that is used for general purposes. The system also has a function that converts TRC motion captured format file into BVH format. Finally, this paper confirms visually through the motion capture data viewer that motion data captured using the Kinect sensor is captured correctly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.35-36
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• 2014

본 논문에서는 Kinect 센서의 동작 인식 기능을 활용한 운동요법 앱을 설계하고 구현한다. 이 앱은 사용자의 상체, 하체 관절의 움직임을 인식하여 체조의 올바른 자세를 배울 수 있도록 한다. 이 앱의 특징은 Kinect Sensor로 인식한 관절 요소를 읽어 들이고, 각 관절의 각도를 계산하여 원하는 동작을 표현할 수 있도록 한다. 또한, 사용자의 동작과 기본 동작을 비교하여 오차 범위 내이면 새로운 동작이 진행되도록 한다. 출력되는 각 동작들은 Library를 이용하여 많은 포즈들을 입력하고 출력할 수 있기 때문에 새로운 포즈를 추가하기에 쉽다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.279-282
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• 2017

Kinect depth sensor, a depth camera developed by Microsoft as a natural user interface for game appeared as a very useful tool in computer vision field. In this paper, due to kinect's depth sensor and its high frame rate, we developed a distance measurement system using Kinect camera to test it for unmanned vehicles which need vision systems to perceive the surrounding environment like human do in order to detect objects in their path. Therefore, kinect depth sensor is used to detect objects in its field of view and enhance the distance measurement system from objects to the vision sensor. Detected object is identified in accuracy way to determine if it is a real object or a pixel nose to reduce the processing time by ignoring pixels which are not a part of a real object. Using depth segmentation techniques along with Open CV library for image processing, we can identify present objects within Kinect camera's field of view and measure the distance from them to the sensor. Tests show promising results that this system can be used as well for autonomous vehicles equipped with low-cost range sensor, Kinect camera, for further processing depending on the application type when they reach a certain distance far from detected objects.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.163-164
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• 2019

본 논문에서는 Kinect Sensor를 활용하여 사용자의 뒤틀린 자세를 교정하는데 도움을 줄 수 있는 어플리케이션을 설계하고 구현한다. 이 어플리케이션은 사용자의 자세 교정 부위 별로 분류하여 제시함으로써 체계적인 교정과 운동 효과를 볼 수 있는 장점이 있다.