• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.851-854
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• 2003

The low power motion estimation for MPEG-4 is a soft-core for hardwired motion estimation block in MPEG-4. This motion estimation is modified by 10 difference mode. So, this motion estimation decrease a power consumption compare conventional step search. This modified 4SS Low power Motion Estimation has been tested and verified to be valid for implementation of FPGA. The average PSNR between the original image and the motion-compensated image is 28.25dB. And Power consumption is 26mW.

• Wind and Structures
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• v.14 no.6
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• pp.499-515
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• 2011

Low-frequency building vibration is known to induce symptoms of motion sickness in some occupants. This paper examines how the adoption of a theory of motion sickness, in conjunction with a dose-response model might inform the real-world problem of managing and designing standards for tall building motion sway. Building designers require an understanding of human responses to low-dosage motion that is not adequately considered by research into motion sickness. The traditional framework of Sensory Conflict Theory is contrasted with Postural Instability Theory. The most severe responses to motion (i.e., vomiting) are not experienced by occupants of wind-excited buildings. It is predicted that typical response sets to low-dosage motion (sleepiness and fatigue), which has not previously been measured in occupants of tall-buildings, are experienced by building occupants. These low-dose symptoms may either be masked from observation by the activity of occupants or misattributed to the demands of a typical working day. An investigation of the real-world relationship between building motion and the observation of low-dose motion sickness symptoms and a degradation of workplace performance would quantify these effects and reveal whether a greater focus on designing for occupant comfort is needed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.81-95
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• 1996

In this paper, we propose a motio estiamtion algorithm using low-resolution quantization to reduce the computation of the full search algorithm. The proposed algorithm consists of the low-resolution search which determins the candidate motion vectors by comparing the low-resolution image and the full-resolution search which determines the motion vector by comparing the full-resolution image on the positions of the candidate motion vectors. The low-resolution image is generated by subtracting each pixel value in the reference block or the search window by the mean of the reference block, and by quantizing it is 2-bit resolution. The candidate motion vectors are determined by counting the number of pixels in the reference block whose quantized codes are unmatched to those in the search window. Simulation results show that the required computational cost of the proposed algorithm is reduced to 1/12 of the full search algorithm while its performance degradation is 0.03~0.12 dB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4624-4644
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• 2019

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.

• Physical Therapy Rehabilitation Science
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• v.10 no.2
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• pp.225-234
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• 2021

Objective: We aimed to identify the effects of proprioceptive neuromuscular facilitation (PNF) stretching on pain, hip range of motion, and functional disability in patients with chronic low back pain. Design: Randomized controlled trial Methods: In total, 45 patients with chronic low back pain were randomly divided into a conventional stretching group (n=22) and a PNF stretching group (n=23). Both interventions were performed three times per week for 6 weeks. Assessments were made using the visual analog scale, Flexion-Abduction-External Rotation test, modified Thomas test, prone hip extension test, and Oswestry disability index before and after the 6-week intervention period. We conducted a paired t-test to compare the within-group findings before and after the intervention. An independent t-test was used to compare the between-group differences. The statistical significance level was set at α=0.05, for all variables. Results: Both groups showed significant improvements in pain, hip range of motion, and functional disability after the intervention (p<0.05). A significant difference was observed in pain, hip range of motion, and functional disability in patients belonging to the PNF stretching group (p<0.05). Conclusions: This study provides evidence that the application of PNF stretching can effectively reduce pain and improve hip range of motion and functional disability in patients with chronic low back pain.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.4
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• pp.247-256
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• 2009

In this paper, a motion detection algorithm which works well in low illumination environment is proposed. By using the level set based bimodal motion segmentation, the algorithm obtains an automatic segmentation of the motion region and the spurious regions due to the large CCD noise in low illumination environment are removed effectively.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.199-202
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• 2001

In this paper, we propose new method of signal processing for the Pulse Oximeter for resistant motion artifact. When measure Oxygen saturation, today Pulse Oximeter is low reality because of patient moving, and it low difficult to filtering because of overlap Oxygen saturation and motion artifact. For we measure high reality Oxygen saturation, we reduces motion artifact. In this paper, we Propose and simulate method of signal processing for the Pulse Oximeter for resistant motion artifact.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.149-156
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• 2004

In this paper, novel power-aware motion estimation is proposed for low-power multimedia communication. In the video compression, motion estimation dominates the total power consumption, where better performance usually requires more power consumption. Among several motion estimation algorithms with different performance and power, the proposed motion estimation adaptively selects the optimal algorithm during run-time, considering the trade-off between performance and power. The proposed motion estimation can be easily applied to various motion estimation algorithms with negligible computation or hardware overhead. According to simulation results, the proposed motion estimation reduces the power consumption to 1/15.7~1/5.6 without performance degradation, when compared to the conventional algorithms.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1587-1596
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• 2016

This paper presents an interactive locomotion controller using motion capture data and inverted pendulum model. Most of the data-driven character controller using motion capture data have two kinds of limitation. First, it needs many example motion capture data to generate realistic motion. Second, it is difficult to make natural-looking motion when characters navigate dynamic terrain. In this paper, we present a technique that uses dimension reduction technique to motion capture data together with the Gaussian process dynamical model (GPDM), and interpolates the low-dimensional data to make final motion. With the low-dimensional data, we can make realistic walking motion with few example motion capture data. In addition, we apply the inverted pendulum model (IPM) to calculate the root trajectory considering the real-time user input upon the dynamic terrain. Our method can be used in game, virtual training, and many real-time applications.

• Journal of the Ergonomics Society of Korea
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• v.17 no.2
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• pp.11-23
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• 1998

Dynamic motion difference between normal subjects and low-back pain (LBP) patients has been investigated in terms of kinematic variables such as range of motion, velocity and acceleration of the back and hip. Ten healthy subjects and ten LBP patients were recruited in this study. Electro-goniometer such as Lumbar Motion Monitor and Hip Monitor have been used for quantitative measurement of the trunk motion during repetitive flexion and extension for ten seconds. Results indicated that the velocity and acceleration of the back and hip were important parameters to quantitatively identify LBP patients. The consistency of cyclic trunk motion and the relationship between the back and hip were measured in terms of Variance Ratio and Phase Angle in order to accurately assess the motion characteristics of LBP patients. In particular, the hip motion has been proven to be a very important factor in describing the kinematics of damaged lower back. The functional evaluation technique suggested in this study will be a tool to assist physicians for an accurate diagnosis and timely rehabilitation along with current image diagnosis techniques.