Munkhjargal Gochoo

Improved global motion estimation via motion vector clustering for video stabilization

Video stabilization technique is often used in handheld multimedia devices, whereas the difficulties in the accurate extraction aspect of global motion vectors restrict its development. This paper proposes a novel video stabilization approach that is based on the shortest spanning path clustering algorithm for effective and reliable estimation of the global motion vectors. As demonstrated in our experimental results, the proposed approach achieves superior stabilized effectiveness compared with the other state-of-the-art approaches based on both qualitative and quantitative measurements.

Indoor activity monitoring system for elderly using RFID and Fitbit Flex wristband

An indoor activity monitoring system for the elderly is proposed in this paper by using a Fitbit Flex wristband (FFW) and an active RFID. Two methods have been presented for identification of an activity place and a best accuracy of 98.89% has been achieved. The activity level of the elderly is evaluated via dissimilarity measurement by employing an activity density map. The presented system has the advantages of avoiding invasion of ones privacy and monitoring the daily activity unobtrusively. Experimental results show the potential of the proposed system for practical application.

Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients’ biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient’s biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.

Design and application of novel morphological filter used in vehicle detection

In this paper we represent our proposed novel morphological filter developed under the scope of Taiwan-Mongolian co-project. We applied the implemented filter in vehicle detection from CCTV video signal. Our goalwas to develop a filter that can reduce the noise in background subtracted binary image, which created by camera shake, and unnecessary moving objects such as wave of the tree etc. We compared our filter performance with morphological open, close, erosion, dilation, and median filters. PSNR (Peak Signal to Noise Ratio) is employed for evaluating the performance of the filters, our filters PSNR was relatively higher (21.39) than the other method. Furthermore, we used our filter for vehicle detection, and detection rate was 100% as the other methods. Thus, we conclude the new filter is sufficient for denoising binary image, and suitable for vehicle detection.

Device-Free Non-Privacy Invasive Classification of Elderly Travel Patterns in a Smart House Using PIR Sensors and DCNN

Single resident life style is increasing among the elderly due to the issues of elderly care cost and privacy invasion. However, the single life style cannot be maintained if they have dementia. Thus, the early detection of dementia is crucial. Systems with wearable devices or cameras are not preferred choice for the long-term monitoring. Main intention of this paper is to propose deep convolutional neural network (DCNN) classifier for indoor travel patterns of elderly people living alone using open data set collected by device-free non-privacy invasive binary (passive infrared) sensor data. Travel patterns are classified as direct, pacing, lapping, or random according to Martino–Saltzman (MS) model. MS travel pattern is highly related with person’s cognitive state, and thus can be used to detect early stage of dementia. We have utilized an open data set that was presented by Center for Advanced Studies in Adaptive Systems project, Washington State University. The data set was collected by monitoring a cognitively normal elderly person by wireless passive infrared sensors for 21 months. First, 117 320 travel episodes are extracted from the data set and classified by MS travel pattern classifier algorithm for the ground truth. Later, 12 000 episodes (3000 for each pattern) were randomly selected from the total episodes to compose training and testing data set. Finally, DCNN performance was compared with seven other classical machine-learning classifiers. The random forest and DCNN yielded the best classification accuracies of 94.48% and 97.84%, respectively. Thus, the proposed DCNN classifier can be used to infer dementia through travel pattern matching.

Development of an emergency medical service system based on wireless networks and real-time traffic information

This study develops a real-time traffic information-based emergency medical service (RTIEMS) system by employing sensor devices, webcam, 2.4 GHz ISM band RF module, ZigBee, GPS, Google Maps, and WiMAX mobile network. In the ambulance, patient biosignals consisting of electrocardiogram (ECG), temperature, oxygen, and pulse can be wirelessly transmitted to the in-car gateway. Then, together with patient real-time video, those biosignals are transmitted via WiMAX mobile network to the server located in the hospital emergency room for immediate first-aid preparation. Furthermore, to avoid jam-packed areas, a traffic guiding subsystem is presented based on the WebGIS that consists of Google Maps and GPS to help patient be delivered to the hospital with shortest time. Experimental results verify the effectiveness of the proposed RTIEMS system in lengthening the golden rescue time; thus significantly enhancing service quality of emergency medical system.