Moon-Jin Jeon

User adaptive hand gesture recognition using multivariate fuzzy decision tree and fuzzy garbage model

Recently, the natural signal of human such as voice or gesture has been applied to the system for assisting disabled and the elderly people. As an example of such kind of system, the Soft Remote Control System has been developed by HWRS-ERC in KAIST [1]. This system is a vision-based hand gesture recognition system for controlling home appliances such as television, lamp and curtain. One of the most important technologies of the system is the hand gesture recognition algorithm. The frequently occurred problems which lower the recognition rate of hand gesture are inter-person variation and wrong recognition of similar gestures. In this paper, we propose multivariate fuzzy decision tree (MFDT) learning and classification algorithm for hand gesture recognition. The similar meaningless gestures are rejected using fuzzy garbage model. To recognize hand gesture of a new user, the most proper recognition model among several well trained models is selected using model selection algorithm and incrementally adapted to the users hand gesture. For the general performance of MFDT as a classifier, we show classification rate using the benchmark data of the UCI repository. The experimental results show the classification and user adaptation performance of proposed algorithm is better than traditional fuzzy decision tree. Also the meaningless gestures are well rejected.

Hand Gesture Recognition Using Multivariate Fuzzy Decision Tree and User Adaptation

As an emerging human-computer interaction HCI technology, recognition of human hand gesture is considered a very powerful means for human intention reading. To construct a system with a reliable and robust hand gesture recognition algorithm, it is necessary to resolve several major difficulties of hand gesture recognition, such as inter-person variation, intra-person variation, and false positive error caused by meaningless hand gestures. This paper proposes a learning algorithm and also a classification technique, based on multivariate fuzzy decision tree MFDT. Efficient control of a fuzzified decision boundary in the MFDT leads to reduction of intra-person variation, while proper selection of a user dependent UD recognition model contributes to minimization of inter-person variation. The proposed method is tested first by using two benchmark data sets in UCI Machine Learning Repository and then by a hand gesture data set obtained from 10 people for 15 days. The experimental results show a discernibly enhanced classification performance as well as user adaptation capability of the proposed algorithm.

A line rate calculation method for arbitrary directional imaging of an Earth observing satellite

For an earth observing satellite, a line rate is the number of lines which the CCD of push broom type camera scans in a second. It can be easily calculated by ground velocity divided by ground sample distance. Accurate calculation of line rate is necessary to obtain high quality image using TDI CCD. The earth observing satellite has four types of imaging missions which are strip imaging, stereo imaging, multi-point imaging, and arbitrary directional imaging. For the first three types of imaging, ground scanning direction is aligned with satellite velocity direction. Therefore, if the orbit propagation and spacecraft attitude information are available, the ground velocity and ground sample distance could be easily calculated. However, the calculation method might not be applicable to the arbitrary directional imaging. In the arbitrary directional imaging mode, the ground velocity is not fixed value which could be directly derived by orbit information. Furthermore, the ground sample distance might not be easily calculated by simple trigonometry which is possible for the other types of imaging. In this paper, we proposed a line rate calculation method for the arbitrary directional imaging. We applied spherical geometry to derive the equation of ground point which is the intersection between the line of sight vector of the camera and earth surface. The derivative of this equation for time is the ground velocity except the factor of earth rotation. By adding this equation and earth rotation factor, the true ground velocity vector could be derived. For the ground sample distance, we applied the equation of circle and ellipse for yaw angle difference. The equation of circle is used for the yaw angle representation on the plane which is orthogonal to the line of sight vector. The equation of ellipse is used for the yaw angle representation on the ground surface. We applied the proposed method to the KOMPSAT-3A (Korea Multi-Purpose Satellite 3A) mission which is the first Korean satellite with optical and infrared sensor. The satellite was launched by a Dnepr on 26 March 2015 and started normal operation on September 2015. The payload of the satellite is AEISS-A(Advanced Earth Imaging Sensor System-A) which has 0.55m GSD for panchromatic image, 2.2m GSD for multi-spectral image, and day-and-night infrared image. The main mission objective of the satellite is providing high resolution electro-optical images and infrared images for GIS application. By applying the proposed method, the line rate error was reduced to about 0.2% from 0.5% of previous method. The arbitrary directional imaging mode became a major operation mode and various application modes including due north directional imaging, pitch steering imaging, pitch step imaging are now developing. These application modes are based on technical achievement of the proposed method. In this paper, the details of line rate calculation method are described. The experimental results show the accuracy of the proposed method is less than 0.2% in average. For the application results, the mission operation of KOMPSAT-3A and arbitrary directional imaging results are described.

Performance Enhancement of a Satellite’s Onboard Antenna Tracking Profile using the Ground Station Searching Method

In satellite operations, stable maneuvering of a satellite’s onboard antenna to prevent undesirable vibrations to the satellite body is required for high-quality high-resolution images. For this reason, the onboard antenna’s angular rate is typically minimized while still satisfying the system requirement that limits the speed of the onboard antenna. In this study, a simple yet effective method, called the ground station searching method, is proposed to reduce the angular rate of a satellite’s onboard antenna. The performance of the proposed method is tested using real flight data from the KOMPSAT-3 satellite. Approximately 83% of arbitrarily selected real flight scenarios from 66 test cases show reductions in the onboard antenna’s azimuth angular rates. Additionally, reliable solutions were consistently obtained within a reasonably acceptable computation time while generating an onboard antenna tracking profile. The obtained results indicate that the proposed method can be used in real satellite operations and can reduce the operational loads on a ground operator. Although the current work only considers the KOMPSAT-3 satellite as a test case, the proposed method can be easily modified and applied to other satellites that have similar operational characteristics.

A Personalized Hand Gesture Recognition System using Soft Computing Techniques

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.