Virtual reconstruction of random moving image capturing points based on chaos embedded particle swarm optimization algorithm

Qu, Chen

doi:10.1016/j.micpro.2020.103069

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…The extraction results of the secondary contour are taken as the initial edge of the active contour model to gradually reduce the energy of the boundary contour. When the energy value reaches the minimum, the obtained edge image is the final target contour of the moving image [22].…”

Section: Contour Feature Extraction From Multimotion Imagesmentioning

confidence: 99%

RETRACTED: Parallax information fusion-based for dance moving image posture extraction [EAI Endorsed Scal Inf Syst (2022), Online First]

Liu¹,

Lin²

2018

ICST Transactions on Scalable Information Systems

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The existing motion image posture contour extraction results have low definition and serious detail loss. To solve this problem, we propose a novel dance moving image posture extraction method based on parallax information fusion. Firstly, the image with motion information is statistically analyzed by using the information fusion process to determine the position of the motion region. After the noise is reduced by morphological processing, the initial motion posture profile is obtained. The parallax between different control points and the center is used as the active contour model to shape the contraction force and expansion force, which can effectively assist the initial edge contour curve to gradually approach the real edge contour. Finally, the contour of the current moving image is extracted from the sequence image contour to obtain the attitude contour of the moving image. The experimental results show that the proposed method can extract the contour of the moving image clearly with less detail loss, which proves that the proposed method has strong practical performance and can effectively find the contour of the moving object.

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Section: Contour Feature Extraction From Multimotion Imagesmentioning

confidence: 99%

RETRACTED: Parallax information fusion-based for dance moving image posture extraction [EAI Endorsed Scal Inf Syst (2022), Online First]

Liu¹,

Lin²

2018

ICST Transactions on Scalable Information Systems

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“…In the multimedia domain (image processing), PSO [28] is used to optimize the scaling factors and the parameter of the improved discrete fractional angular transform in watermark schemes. A chaos-embedded PSO (CEPS) [29] is introduced, which can improve the interpolation precision and reduce the calculation time of interpolation to realize the fast reconstruction of the target 3D image based on biomechanical characteristics. In the medical imaging and deep learning domain, Ref.…”

Section: Embedded Particle Swarm Optimizationmentioning

confidence: 99%

Embedded PSO for Solving FJSP on Embedded Environment (Industry 4.0 Era)

et al. 2022

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Since of the advent of Industry 4.0, embedded systems have become an indispensable component of our life. However, one of the most significant disadvantages of these gadgets is their high power consumption. It was demonstrated that making efficient use of the device’s central processing unit (CPU) enhances its energy efficiency. The use of the particle swarm optimization (PSO) over an embedded environment achieves many resource problems. Difficulties of online implementation arise primarily from the unavoidable lengthy simulation time to evaluate a candidate solution. In this paper, an embedded two-level PSO (E2L-PSO) for intelligent real-time simulation is introduced. This algorithm is proposed to be executed online and adapted to embedded applications. An automatic adaptation of the asynchronous embedded two-level PSO algorithm to CPU is completed. The Flexible Job Shop Scheduling Problem (FJSP) is selected to solve, due to its importance in the Industry 4.0 era. An analysis of the run-time performance on handling E2L-PSO over an STM32F407VG-Discovery card and a Raspberry Pi B+ card is conducted. By the experimental study, such optimization decreases the CPU time consumption by 10% to 70%, according to the CPU reduction needed (soft, medium, or hard reduction).

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“…Therefore, the Pro/E model must be simplified. According to the virtual body, each object in the above picture can be extracted, and then, a meaningful name is given to each object, and the link is carried out according to the link relationship in the above 4 Wireless Communications and Mobile Computing picture. For the object that needs to be rotated, set the rotation axis, and you can easily move the rotation axis to a suitable position.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

“…Human body sports models based on three-dimensional images can be divided into two types: broad sense and narrow sense. The broad sense of motion capture generally includes the capture of facial expressions, gestures, and human bone joints, while the narrowly defined human body sports model based on three-dimensional images only refers to the capture of human bone joint motion [4]. With the gradual maturity of the development of sports model technology based on 3D images, there are already many methods to capture motion, many of which have also been applied to actual projects (such as games, film and television animation, new generation of human-computer interaction, and action recognition) [5].…”

Section: Introductionmentioning

confidence: 99%

Research and Implementation of the Sports Analysis System Based on 3D Image Technology

Wang

Gao

Liu

2021

Wireless Communications and Mobile Computing

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On the basis of existing research, this paper analyzes the algorithms and technologies of 3D image-based sports models in depth and proposes a fusion depth map in view of some of the shortcomings of the current hot spot sports model methods based on 3D images. We use the 3D space to collect the depth image, remove the background from the depth map, recover the 3D motion model from it, and then build the 3D model database. In this paper, based on the characteristics of continuity in space and smoothness in time of a rigid body moving target, a reasonable rigid body target motion hypothesis is proposed, and a three-dimensional motion model of a rigid body target based on the center of rotation of the moving target and corresponding motion is designed to solve the equation with parameters. In the case of unknown motion law, shape, structure, and size of the moving target, this algorithm can achieve accurate measurement of the three-dimensional rigid body motion target’s self-rotation center and related motion parameters. In the process of motion parameter calculation, the least square algorithm is used to process the feature point data, thereby reducing the influence of noise interference on the motion detection result and correctly completing the motion detection task. The paper gives the measurement uncertainty of the stereo vision motion measurement system through simulated and real experiments. We extract the human body motion trajectory according to the depth map and establish a motion trajectory database. For using the recognition algorithm of the sports model based on the 3D image, we input a set of depth map action sequences. After the above process, the 3D motion model is obtained and matched with the model in the 3D motion model database, and the sequence with the smallest distance is calculated. The corresponding motion trajectory is taken as the result of motion capture, and the efficiency of this system is verified through experiments.

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Virtual reconstruction of random moving image capturing points based on chaos embedded particle swarm optimization algorithm

Cited by 10 publications

References 14 publications

RETRACTED: Parallax information fusion-based for dance moving image posture extraction [EAI Endorsed Scal Inf Syst (2022), Online First]

RETRACTED: Parallax information fusion-based for dance moving image posture extraction [EAI Endorsed Scal Inf Syst (2022), Online First]

Embedded PSO for Solving FJSP on Embedded Environment (Industry 4.0 Era)

Research and Implementation of the Sports Analysis System Based on 3D Image Technology

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