• ETRI Journal
• /
• v.30 no.3
• /
• pp.421-431
• /
• 2008

In this paper, we offer a new technique to discover frequent spatiotemporal patterns from a moving object database. Though the search space for spatiotemporal knowledge is extremely challenging, imposing spatial and timing constraints on moving sequences makes the computation feasible. The proposed technique includes two algorithms, AllMOP and MaxMOP, to find all frequent patterns and maximal patterns, respectively. In addition, to support the service provider in sending information to a user in a push-driven manner, we propose a rule-based location prediction technique to predict the future location of the user. The idea is to employ the algorithm AllMOP to discover the frequent movement patterns in the user's historical movements, from which frequent movement rules are generated. These rules are then used to estimate the future location of the user. The performance is assessed with respect to precision and recall. The proposed techniques could be quite efficiently applied in a location-based service (LBS) system in which diverse types of data are integrated to support a variety of LBSs.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.9
• /
• pp.2057-2064
• /
• 2010

With the development of wireless network technology, the location information of a spatiotemporal object which changes their location is used in various application. Each spatiotemporal object has many location information, hence it is inefficient to search all trajectory information of spatiotemporal objects for a range query. In this paper, we propose an efficient method which divides a trajectory and stores its division data on restricted storage space. Using suboptimal split algorithm, an extended split algorithm that minimizes the volume of EMBRs(Extended Minimum Bounding Box) is designed and simulated. Our experimental evaluation confirms the effectiveness and efficiency of our proposed splitting policy

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.10
• /
• pp.2188-2194
• /
• 2011

With the development of wireless network technology, Storing the location information of a spatiotemporal object was very necessary. Each spatiotemporal object has many unnecessariness location information, hence it is inefficient to search all trajectory information of spatiotemporal objects. In this paper, we propose an efficient method which increase searching efficiency. Using EMBR(Extend Minimun Bounding Rectangle), an LinearMarge split algorithm that minimizes the volume of MBRs is designed and simulated. Our experimental evaluation confirms the effectiveness and efficiency of our proposed splitting policy.

• Journal of the Institute of Convergence Signal Processing
• /
• v.15 no.4
• /
• pp.128-134
• /
• 2014

In this paper, we propose a detection method of the leukocyte motions in a microvessel by using spatiotemporal image analysis. The leukocyte motions that adhere to blood vessel walls can be visualized to move along the blood vessel wall's contours in a sequence of images. In this proposal method, we use the constraint that the leukocytes move along the blood vessel wall's contours and detect the leukocyte motions by using the spatiotemporal image analysis method. The generated spatiotemporal image is processed by a special-purpose orientation-selective filter and then subsequent grouping processes are done. The subsequent grouping processes select and group the leukocyte trace segments among all the segments obtained by simple thresholding and skeletonizing operations. Experimental results show that the proposed method can stably detect the leukocyte motions even when multiple leukocyte traces intersect each other.

• Physical Therapy Korea
• /
• v.20 no.4
• /
• pp.40-46
• /
• 2013

The purpose of this study was to determine which spatiotemporal gait parameters obtained during hemiplegic walking could be a predictive factor for the Timed Up and Go test (TUG). Two hundreds nine subjects who had suffered a stroke were recruited for this study. They were participated in two assessments; the TUG test and gait analysis. The relationship between the TUG test and spatiotemporal parameters was analyzed using Pearson's correlation coefficients. In addition, to predict the spatiotemporal gait parameters that correlated most with the TUG scores, we used multiple linear regression analyses (stepwise method). The results show that the normalized velocity was strongly correlated with the TUG performance (r=-.72, p<.001). Additionally, single support percentage (SSP), double support percentage (DSP), step time difference (STD), and step length difference (SLD) significantly were correlated with the TUG test. Normalized velocity, STD, DSP of affected side, and SSP of non-affected side explained 53%, 8%, 3%, 2%, of variance in the TUG test respectively. In conclusion, an increase in gait velocity and a decrease in STD would be effective indicators of improvement on the functional mobility in the stroke rehabilitation.

• Journal of Information Processing Systems
• /
• v.17 no.2
• /
• pp.337-351
• /
• 2021

Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.

• Physical Therapy Rehabilitation Science
• /
• v.11 no.1
• /
• pp.105-112
• /
• 2022

Objective: Nonspecific low back pain (NS-LBP) causes pain and disability, affecting the neuromuscular system and altering gait patterns. The purpose of this study is to investigate the effect of improvement of low back pain symptoms through physical therapy on foot pressure and spatiotemporal gait parameters. Design: A pilot study. Methods: Participants received manual therapy and supervised therapeutic exercise, which consisted of 12 sessions for 6 weeks. Participants were assessed for pain intensity (a numeric pain rating scale), disability index (oswestry disability index), and spatiotemporal gait parameters before and after intervention. Wilcoxon signed rank test was used to analyze the before-and-after differences in a single group. Results: All seven NS-LBP patients completed the study without dropout. After six weeks of physical therapy, the numeric pain rating scale and oswestry disability index showed significant improvement (Z= -2.388, P=0.017). There was no significant improvement in both static and dynamic conditions in foot pressure (P>0.05). However, in the spatiotemporal gait parameters, there were significant differences in all variables except the right stance phase and left mid stance (P<0.05). Conclusions: In our pilot study, 12 sessions of physical therapy in NS-LBP patients improved gait quilty in spatiotemporal gait parameters. Similarly, it has resulted in clinically positive improvements in pain and disability.

• The KIPS Transactions:PartD
• /
• v.8D no.2
• /
• pp.105-116
• /
• 2001

Moving objects are spatiotemporal data that location and shape of spatial objects are changed continuously over time. If spatiotemporal moving objects are managed by conventional database system, moving objects management systems have two problems as follows. First, update for location information changed over time is occurred frequently. Second, past and future information of moving objects are not provided by system because only current state of objects is stored in the system. Therefore, in this paper, we propose a spatiotemporal moving objects management system which is able to not only manage historical information of moving objects without frequent update, but also provide all location information about past, current, and near future. In the proposed system, information of moving objects are divided into location information for representing location and motion information for representing moving habits. Especially, we propose the method which can search location information all objects by use of changing process algorithms with minimum history information. Finally, we applied the proposed method to battlefield analysis system, as the result of experiment, we knew that past, current, and near future location information for moving objects are managed by relational database and GIS system.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.1
• /
• pp.11-20
• /
• 1999

Because conventional spatial databases process the spatial information that is valid at current time, it is difficult to manage historical information efficiently which has been changed from the past to current. Recently, there are rapid increasing of interest to solve this problem so that makes databases to support historical information as well as spatial management at the same time. It can be eventually used in a various application areas. The formal semantics in a database is used to represent database structures and operations in order to prove the correctiveness of them in terms or mathematics. It also plays an important role in database to design a database and database management system. So in this paper, we suggest spatiotemporal domain, object, data, and spatiotemporal geometric/topological operations. And we not only formalize relational algebra/calculus using formal semantics for a spatiotemporal data model, but also show the example of real orld with them.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.9
• /
• pp.99-109
• /
• 2016

This paper presents a method for generating spatiotemporal images to detect the leukocyte motions in a microvessel. By using the constraint that the leukocytes move along the contour line of a blood vessel wall, the method detects leukocyte motions and then generates spatiotemporal images. the translational motion by a movement in vivo is removed first by the template matching method. Next, a blood vessel region is detected by the automatic threshold selection method to binarize the temporal variance image, then a blood vessel wall's contour is expressed by B-spline function. With the detected blood vessel wall's contour as an initial curve, the plasma layer of the best accurate position is determined to be the spatial axis by snake. Finally, the spatiotemporal images are generated. The experimental results show the spatiotemporal images are generated effectively through the comparison of each step of three image sequences.