• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.262-263
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• 2015

본 논문에서는 마이크로소프트 키넥트 센서를 이용한 실시간 성능의 3차원 환경 복원 알고리즘을 소개한다. 기존의 멀티키넥트 시스템을 확장하여 총 열두대의 키넥트를 사용하는데, 키넥트의 높은 대역폭 문제를 해결하기 위하여 키넥트가 여섯 대씩 연결된 두 대의 데스크탑을 UDP 통신으로 연결하였고, 각 키넥트로부터 들어오는 3차원 포인트클라우드로부터 확률적인 3차원 환경복원을 하기 위하여 옥토맵 알고리즘을 차용하였다. 또한, GPU를 연산에 활용함으로써 실시간 성능을 확보하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.558-567
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• 2017

In this research, we developed an efficient real-time human exercise pose estimation system using multiple Kinects. The main objective of this system is to measure and recognize the user's posture (such as knee curl or lunge) more accurately by employing Kinects on the front and the sides. Especially it is designed as an extensible and modular method which enables to support various additional postures in the future. This system is configured as multiple clients and the Unity3D server. The client processes Kinect skeleton data and send to the server. The server performs the multiple-Kinect calibration process and then applies the pose estimation algorithm based on the Kinect-based posture recognition model using feature extractions and the weighted averaging of feature values for different Kinects. This paper presents the design and implementation of the human exercise pose estimation system using multiple Kinects and also describes how to build and execute an interactive Unity3D exergame.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.827-836
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• 2012

After successful advent of Microsoft's Kinect, many interactive contents that control user's 3D avatar motions in realtime have been created. However, due to the Kinect's intrinsic IR projection problem, users are restricted to face the sensor directly forward and to perform all motions in a standing-still position. These constraints are main reasons that make it almost impossible for the 3D character to navigate the virtual environment, which is one of the most required functionalities in games. This paper proposes a new method that makes 3D character navigate the virtual environment with highly realistic motions. First, in order to find out the user's intention of navigating the virtual environment, the method recognizes walking-in-place motion. Second, the algorithm applies the motion splicing technique which segments the upper and the lower motions of character automatically and then switches the lower motion with pre-processed motion capture data naturally. Since the proposed algorithm can synthesize realistic lower-body walking motion while using motion capture data as well as capturing upper body motion on-line puppetry manner, it allows the 3D character to navigate the virtual environment realistically.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.255-261
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• 2014

Advances of digital device technology such as digital cameras, smart phones and tablets, provide convenience way for people to take pictures during his/her life. Photo data is being spread rapidly throughout the social network, causing the excessive amount of data available on the internet. Photo retrieval is categorized into three types, which are: keyword-based search, example-based search, visualize query-based search. The commonly used multimedia search methods which are implemented on Smart TV are adapting the previous methods that were optimized for PC environment. That causes some features of the method becoming irrelevant to be implemented on Smart TV. This paper proposes a novel Visual Query-based Photo Retrieval Method in Smart TV Environment using a motion sensing input device known as Kinect Sensor. We detected hand gestures using kinect sensor and used the information to mimic the control function of a mouse. The average precision and recall of the proposed system are 81% and 80%, respectively, with threshold value was set to 0.7.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1493-1503
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• 2018

We propose an object recognition system and experiential game contents using Kinect to maximize object recognition rate by utilizing underwater robots. we implement an ice hockey game based on object-aware interactive contents to validate the excellence of the proposed system. The object recognition system, which is a preprocessor module, is composed based on Kinect and OpenCV. Network sockets are utilized for object recognition communications between C/S. The problem of existing research, degradation of object recognition at long distance, is solved by combining the system development method suggested in the study. As a result of the performance evaluation, the underwater robot object recognized all target objects (90.49%) with 80% of accuracy from a 2m distance, revealing 42.46% of F-Measure. From a 2.5m distance, it recognized 82.87% of the target objects with 60.5% of accuracy, showing 34.96% of F-Measure. Finally, it recognized 98.50% of target objects with 59.4% of accuracy from a 3m distance, showing 37.04% of F-measure.