• Journal of IKEEE
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• v.24 no.4
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• pp.1109-1116
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• 2020

The matching score evaluating human copying ability can be a good measure to check children's developmental stages, or sports movements like golf swing and dance, etc. It also can be used as HCI for AR, VR applications. This paper presents a method to evaluate the motion similarity between demonstrator who initiates movement and participant who follows the demonstrator action. We present a quantification method of the similarity which utilizes Euclidean L2 distance of Openpose keypoins vector similarity. The proposed method adapts DTW, thus can flexibly cope with the time delayed motions.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.309-316
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• 2004

In this paper, we proposed the TDS(T-shape Diamond Search) based on the directions of above, below, left and right points to estimate the motion vector fast and more correctly in this method, we exploit the facts that most motion vectors are enclosed in a circular region with a radius of 2 fixels around search center(0,0). At first, the 4 points in the above, below, left and right around the search center is calculated to decide the point of the MBD(Minimum Block Distortion). And then w. above point of the MBD is checked to calculate the SAD. If the SAD of the above point is less than the previous MBD, this process is repeated. Otherwise, the right and left points of MBD are calculated to decide The points that have the MBD between right point and left point. Above processes are repeated to the predicted direction for motion estimation. Especially, if the motions of image are concentrated in the crossing directions, the points of other directions are omitted. As a result, we can estimate motion vectors fast. Experiments show that the speedup improvement of the proposed algorithm over Diamond Search algorithm(DS) and HEXgon Based Search(HEXBS) can be up to 38∼50％ while maintaining similar image Quality.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.63-71
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• 2012

Recently, web portals have been offering georeferenced SLI(Street-Level Imagery) services, such as Google Streetview. The SLI has a distinctive strength over aerial images or vector maps because it gives us the same view as we see the real world on the street. Based on the characteristic, applicability of the SLI can be increased substantially through conflation with other spatial datasets. However, spatial inconsistency between different datasets is the main reason to decrease the quality of conflation when conflating them. Therefore, this research aims to remove the spatial inconsistency to conflate an SLI with a widely used 2D vector map. The removal of the spatial inconsistency is conducted through three sub-processes of (1) road intersection matching between the SLI trace and the road layer of the vector map for detecting CPPs(Control Point Pairs), (2) inaccurate CPPs filtering by analyzing the trend of the CPPs, and (3) local alignment using accurate CPPs. In addition, we propose an evaluation method suitable for conflation result including an SLI, and verify the effect of the removal of the spatial inconsistency.

• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.1-11
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• 2008

This paper detected the characteristics of motion vector to support efficient content -based video search of video. Traditionally, the present frame of a video was divided into blocks of equal size and BMA (block matching algorithm) was used, which predicts the motion of each block in the reference frame on the time axis. However, BMA has several restrictions and vectors obtained by BMA are sometimes different from actual motions. To solve this problem, the foil search method was applied but this method is disadvantageous in that it has to make a large volume of calculation. Thus, as an alternative, the present study extracted the Spatio-Temporal characteristics of Motion Vector Spatio-Temporal Correlations (MVSTC). As a result, we could predict motion vectors more accurately using the motion vectors of neighboring blocks. However, because there are multiple reference block vectors, such additional information should be sent to the receiving end. Thus, we need to consider how to predict the motion characteristics of each block and how to define the appropriate scope of search. Based on the proposed algorithm, we examined motion prediction techniques for motion compensation and presented results of applying the techniques.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.247-259
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• 2000

This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.117-126
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• 2010

In the case of failure images with controlling lighting like backlighting and excessive frontlinghting, the compensation scheme for a specific area in an image is required. The interested region is first selected by user in our method to compensate the first frame. Then we define the matching function of brightness and energy function is proposed with weight of matching function and the relationship among the neighbors. Finally, the energy is minimized by the graph-cut algorithm to compensate the brightness of the first frame. Other frames are straightforwardly compensated using the results of the first frame. The brightness variations of the previous frame is transmitted to the next frame via motion vectors. The reliability of the brightness variation is calculated based on the motion vector reliability. Video compensation result is achieved by the process of the image case. Simulation show that the proposed algorithm provides more natural results than the conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.868-875
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• 2003

In this paper, enhanced multiresolution motion estimation(MRME) using reduction of one-pixel shift in wavelet domain is proposed. Conventional multiresolution motion estimation using hierarchical relationship of wavelet coefficient has difficulty for accurate motion estimation due to shift-variant property by decimation process of the wavelet transform. Therefore, to overcome shift-variant property of wavelet coefficient, two level wavelet transform is performed. In order too reduce one-pixel shift on low band signal, S$_4$ band is interpolated by inserting average value. Secondly, one level wavelet transform is applied to the interpolated S$_4$ band. To estimate initial motion vector, block matching algorithm is applied to low band signal S$_{8}$. Multiresolution motion estimation is performed at the rest subbands in low level. According to the experimental results, proposed method showed 1-2dB improvement of PSNR performance at the same bit rate as well as subjective quality compared with the conventional multiresolution motion estimation(MRME) methods and full-search block matching in wavelet domain.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.71-78
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• 2021

Purpose: To evaluate the inter-fractional position and respiratory reproducibility of lung and liver tumors using pressure conserving type(P-type) abdominal compressor in volumetric modulated arc therapy(VMAT). Materials and methods: Six lung cancer patients and three liver cancer patients who underwent VMAT using a P-type abdominal compressor were included in this study. Cone-beam computed tomography(CBCT) images were acquired before each treatment and compared with planning CT images to evaluate the inter-fractional position reproducibility. The position variation was defined as the difference of position shift values between target matching and bone matching. 4-dimensional cone-beam computed tomography(4D CBCT) images were acquired weekly before treatment and compared with planning 4DCT images to evaluate the inter-fractional respiratory reproducibility. The respiratory variation was calculated by the magnitude of excursions by breathing. Results: The mean ± standard deviation(SD) of overall position variation values, 3D vector in the three translational directions were 1.1 ± 1.4 mm and 4.5 ± 2.8 mm for the lung and liver, respectively. The mean ± SD of respiratory variation values were 0.7 ± 3.4 mm (p = 0.195) in the lung and 3.6 ± 2.6 mm (p < 0.05) in the liver. Conclusion: The use of P-type compressor in lung and liver VMAT was effective for stable control of inter-fractional position and respiratory variation by reproduction of abdominal compression. Appropriate PTV margin must be considered in treatment planning, and image guidance before each treatment are required in order to obtain more stable reproducibility