Ig-Jae Kim

Bio: Ig-Jae Kim is an academic researcher from Korea Institute of Science and Technology. The author has contributed to research in topics: Facial recognition system & Augmented reality. The author has an hindex of 16, co-authored 131 publications receiving 1717 citations. Previous affiliations of Ig-Jae Kim include Korea University & University of Science and Technology.

Indoor location sensing using geo-magnetism

Abstract: We present an indoor positioning system that measures location using disturbances of the Earth's magnetic field caused by structural steel elements in a building. The presence of these large steel members warps the geomagnetic field in a way that is spatially varying but temporally stable. To localize, we measure the magnetic field using an array of e-compasses and compare the measurement with a previously obtained magnetic map. We demonstrate accuracy within 1 meter 88% of the time in experiments in two buildings and across multiple floors within the buildings. We discuss several constraint techniques that can maintain accuracy as the sample space increases.

Mobile health monitoring system based on activity recognition using accelerometer

Abstract: We propose a new method to recognize a user’s activities of daily living with accelerometers and RFID sensor. Two wireless accelerometers are used for classification of five human body states using decision tree, and detection of RFID-tagged objects with hand movements provides additional instrumental activity information. Besides, we apply our activity recognition module to the health monitoring system. We derive linear regressions for each activity by finding the correlations between the attached accelerometers and the expended calories calculated from gas exchange analyzer under different activities. Finally, we can predict the expended calories more efficiently with only accelerometer sensor depend on the recognized activity. We implement our proposed health monitoring module on smart phones for better practical use.

Detecting driver drowsiness using feature-level fusion and user-specific classification

Abstract: Accurate classification of eye state is a prerequisite for preventing automobile accidents due to driver drowsiness. Previous methods of classification, based on features extracted for a single eye, are vulnerable to eye localization errors and visual obstructions, and most use a fixed threshold for classification, irrespective of variations in the driver's eye shape and texture. To address these deficiencies, we propose a new method for eye state classification that combines three innovations: (1) extraction and fusion of features from both eyes, (2) initialization of driver-specific thresholds to account for differences in eye shape and texture, and (3) modeling of driver-specific blinking patterns for normal (non-drowsy) driving. Experimental results show that the proposed method achieves significant improvements in detection accuracy.

Activity Recognition Using Wearable Sensors for Elder Care

Abstract: We propose a novel method to recognize a user?s activities of daily living with accelerometers and RFID sensor. Two wireless accelerometers are used for the classification of 5 human body states using decision tree, and detection of RFID tagged objects with hand movement provides additional object related hand motion information. To do this, we used Bluetooth based wireless triaxial accelerometers and iGrabber which is a glove type RFID reader. Our experiments show that our method can be applicable to a real environment with strong confidence.

Interactive presentation system

Abstract: The present invention discloses an interactive presentation system which allows a presenter to perform a presentation while having various interactions directly with presentation material images in real time through a gesture or/and voice The interactive presentation system comprises: an active infrared camera; a command recognition system connected to the active infrared camera; and an image synthesis system connected to the active infrared camera and the command recognition system The presentation system may further comprises a stereo camera set for properly synthesizing a presenter in a 3D image and a 3D motion system By this configuration, it is possible to embody an interactive presentation system in which a command through a presenter's gesture or voice is processed in real time and the image of the presenter is synthesized in a presentation material screen in real time, and accordingly the audiovisual effect is maximized

Exercise Physiology: Energy, Nutrition and Human Performance

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Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons

Abstract: The growing commercial interest in indoor location-based services (ILBS) has spurred recent development of many indoor positioning techniques. Due to the absence of global positioning system (GPS) signal, many other signals have been proposed for indoor usage. Among them, Wi-Fi (802.11) emerges as a promising one due to the pervasive deployment of wireless LANs (WLANs). In particular, Wi-Fi fingerprinting has been attracting much attention recently because it does not require line-of-sight measurement of access points (APs) and achieves high applicability in complex indoor environment. This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment. Regarding advanced techniques to localize users, we present how to make use of temporal or spatial signal patterns, user collaboration, and motion sensors. Regarding efficient system deployment, we discuss recent advances on reducing offline labor-intensive survey, adapting to fingerprint changes, calibrating heterogeneous devices for signal collection, and achieving energy efficiency for smartphones. We study and compare the approaches through our deployment experiences, and discuss some future directions.

No need to war-drive: unsupervised indoor localization

Abstract: We propose UnLoc, an unsupervised indoor localization scheme that bypasses the need for war-driving. Our key observation is that certain locations in an indoor environment present identifiable signatures on one or more sensing dimensions. An elevator, for instance, imposes a distinct pattern on a smartphone's accelerometer; a corridor-corner may overhear a unique set of WiFi access points; a specific spot may experience an unusual magnetic fluctuation. We hypothesize that these kind of signatures naturally exist in the environment, and can be envisioned as internal landmarks of a building. Mobile devices that "sense" these landmarks can recalibrate their locations, while dead-reckoning schemes can track them between landmarks. Results from 3 different indoor settings, including a shopping mall, demonstrate median location errors of 1:69m. War-driving is not necessary, neither are floorplans the system simultaneously computes the locations of users and landmarks, in a manner that they converge reasonably quickly. We believe this is an unconventional approach to indoor localization, holding promise for real-world deployment.