• Title/Summary/Keyword: Motion similarity

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Human Primitive Motion Recognition Based on the Hidden Markov Models (은닉 마르코프 모델 기반 동작 인식 방법)

  • Kim, Jong-Ho;Yun, Yo-Seop;Kim, Tae-Young;Lim, Cheol-Su
    • Journal of Korea Multimedia Society
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    • v.12 no.4
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    • pp.521-529
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    • 2009
  • In this paper, we present a vision-based human primitive motion recognition method. It models the reference motion patterns, recognizes a user's motion, and measures the similarity between the reference action and the user's one. In order to recognize a motion, we provide a pattern modeling method based on the Hidden Markov Models. In addition, we provide a similarity measurement method between the reference motion and the user's one using the editing distance algorithm. Experimental results show that the recognition rate of ours is above 93%. Our method can be used in the motion recognizable games, the motion recognizable postures, and the rehabilitation training systems.

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A Quantification Method of Human Body Motion Similarity using Dynamic Time Warping for Keypoints Extracted from Video Streams (동영상에서 추출한 키포인트 정보의 동적 시간워핑(DTW)을 이용한 인체 동작 유사도의 정량화 기법)

  • Im, June-Seok;Kim, Jin-Heon
    • 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.

Background Initialization by Spatiotemporal Similarity

  • Park, Goo-Man
    • Journal of Broadcast Engineering
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    • v.12 no.3
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    • pp.289-292
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    • 2007
  • A background initialization algorithm based on the spatiotemporal similarity measure in a motion tracking system is proposed. From the accumulated difference between the base frame and the other frames in a subinterval, the regions affected by moving objects are located. The median is applied over the subsequence in the subinterval in which co-located regions share the similarity. The outputs from each subinterval are filtered by second stage median filter. The proposed method showed good results even in the busy and crowded sequences where the real background does not exit.

Region Merging based on Temporal Motion Analysis (시간적 움직임 정보를 이용한 영역 합병)

  • 이동재;정진영김재희
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.903-906
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    • 1998
  • We propose a new method for merging partical regions which have similar motion characteristics. In the proposed method, the trajectories of each partial regions are computed and the regions consisting a same object are merged by a similarity function defined in this paper. The similarity function is defined to take into consideration the motion characteristics of the trajectories. The proposed method shows good performance when the regions of an object show little variation in size and shape.

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Self-similarity in the equation of motion of a ship

  • Lee, Gyeong Joong
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.6 no.2
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    • pp.333-346
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    • 2014
  • If we want to analyze the motion of a body in fluid, we should use rigid-body dynamics and fluid dynamics together. Even if the rigid-body and fluid dynamics are each self-consistent, there arises the problem of self-similar structure in the equation of motion when the two dynamics are coupled with each other. When the added mass is greater than the mass of a body, the calculated motion is divergent because of its self-similar structure. This study showed that the above problem is an inherent problem. This problem of self-similar structure may arise in the equation of motion in which the fluid dynamic forces are treated as external forces on the right hand side of the equation. A reconfiguration technique for the equation of motion using pseudo-added-mass was proposed to resolve the self-similar structure problem; specifically for the case when the fluid force is expressed by integration of the fluid pressure.

SIMILAR AND SELF-SIMILAR CURVES IN MINKOWSKI n-SPACE

  • OZDEMIR, MUSTAFA;SIMSEK, HAKAN
    • Bulletin of the Korean Mathematical Society
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    • v.52 no.6
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    • pp.2071-2093
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    • 2015
  • In this paper, we investigate the similarity transformations in the Minkowski n-space. We study the geometric invariants of non-null curves under the similarity transformations. Besides, we extend the fundamental theorem for a non-null curve according to a similarity motion of ${\mathbb{E}}_1^n$. We determine the parametrizations of non-null self-similar curves in ${\mathbb{E}}_1^n$.

The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation

  • Jonghyuk, Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.39-47
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    • 2023
  • In this paper, we propose a method to measure the similarity between golf swings in videos. As it is known that deep learning-based artificial intelligence technology is effective in the field of computer vision, attempts to utilize artificial intelligence in video-based sports data analysis are increasing. In this study, the joint coordinates of a person in a golf swing video were obtained using a deep learning-based pose estimation model, and based on this, the similarity of each swing segment was measured. For the evaluation of the proposed method, driver swing videos from the GolfDB dataset were used. As a result of measuring swing similarity by pairing swing videos of a total of 36 players, 26 players evaluated that their other swing sequence was the most similar, and the average ranking of similarity was confirmed to be about 5th. This ensured that the similarity could be measured in detail even when the motion was performed similarly.

Deep Learning and Color Histogram based Fire and Smoke Detection Research

  • Lee, Yeunghak;Shim, Jaechang
    • International journal of advanced smart convergence
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    • v.8 no.2
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    • pp.116-125
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    • 2019
  • The fire should extinguish as soon as possible because it causes economic loss and loses precious life. In this study, we propose a new atypical fire and smoke detection algorithm using deep learning and color histogram of fire and smoke. First, input frame images obtain from the ONVIF surveillance camera mounted in factory search motion candidate frame by motion detection algorithm and mean square error (MSE). Second deep learning (Faster R-CNN) is used to extract the fire and smoke candidate area of motion frame. Third, we apply a novel algorithm to detect the fire and smoke using color histogram algorithm with local area motion, similarity, and MSE. In this study, we developed a novel fire and smoke detection algorithm applied the local motion and color histogram method. Experimental results show that the surveillance camera with the proposed algorithm showed good fire and smoke detection results with very few false positives.

Spatio-temporal video segmentation using a joint similarity measure (결합 유사성 척도를 이용한 시공간 영상 분할)

  • 최재각;이시웅;조순제;김성대
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.6
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    • pp.1195-1209
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    • 1997
  • This paper presents a new morphological spatio-temporal segmentation algorithm. The algorithm incorporates luminance and motion information simultaneously, and uses morphological tools such as morphological filtersand watershed algorithm. The procedure toward complete segmentation consists of three steps:joint marker extraction, boundary decision, and motion-based region fusion. First, the joint marker extraction identifies the presence of homogeneours regions in both motion and luminance, where a simple joint marker extraction technique is proposed. Second, the spatio-temporal boundaries are decided by the watershed algorithm. For this purposek, a new joint similarity measure is proposed. Finally, an elimination ofredundant regions is done using motion-based region function. By incorporating spatial and temporal information simultaneously, we can obtain visually meaningful segmentation results. Simulation results demonstratesthe efficiency of the proposed method.

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A Study of Symmetry in the Patterns of Muscle Coordination and Interjoint Coordination in the Upper Limb Activity Among Subjects With Stroke (뇌졸중 환자의 상지에서 근육협응 패턴과 관절협응 패턴의 유사성에 관한 연구)

  • Lee, Jung-Ah;Shin, Hwa-Kyung;Chung, Yi-Jung;Cho, Sang-Hyun
    • Physical Therapy Korea
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    • v.13 no.1
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    • pp.54-60
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    • 2006
  • This study aimed to compare movement patterns of shoulder joints between the right and left symmetry in stroke patients and control subjects. This study proposes use of the voluntary response index (VRI) calculated from quantitative analysis of surface electromyographic (sEMG) and motion data recorded during voluntary movement as a feeding task. The VRI is comprised of two numeric values, one derived from the total muscle activity recorded for the voluntary motor task (magnitude), and the other from the sEMG distribution across the recorded muscles with the similarity index (SI). Five stroke patients and five age-matched healthy controls were recruited. Feeding motion was performed using the provided spoon five times with rests taken on a chair in between tasks. EMG data were digitized and analyzed on the basis of the root mean square (RMS) envelope of activity. The average amplitude of responses was calculated. Responsiveness and clinically meaningful levels of discrimination between stroke patients and control for EMG magnitude and SI were determined. The similarity index of the results from two successive examinations of both sides apart for stroke patients and control subjects were .86 and .95 in motion analysis and .84 and .99 in electromyographic analysis. The SI of sEMG data and motion data was significantly correlated in stroke patients. The data suggest that SI is a sensitive program for comparing and analyzing the symmetry of muscle activity and motion in both sides. This analysis method has a clinical value in grading muscular activity and movement impairment after brain injury.

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