VLSI Implementation of a High-Performance Nonlinear Image Scaling Algorithm

Khalaf, Osamah Ibrahim; Romero, Carlos Andrés Tavera; Pazhani, A. Azhagu Jaisudhan; Vinuja, G.

doi:10.1155/2021/6297856

Cited by 67 publications

(53 citation statements)

References 36 publications

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“…By analyzing the experimental result data in Figure 6, it can be seen that the correlation coefficients of action and music beat matching in the sample dance video are different by using the methods of this paper, in [26], and in [27]. e correlation coefficient of this approach is the closest to 1 and the greatest is about 0.98, but the correlation coefficient of the other two ways is lower, demonstrating the usefulness of this method.…”

Section: Analysis Of Experimental Resultsmentioning

confidence: 85%

Recognition Method of Matching Error between Dance Action and Music Beat Based on Data Mining

Zhu

2022

Security and Communication Networks

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Aiming at the problems of low error recognition accuracy and low correlation of data matching in the existing dance action and music beat matching error recognition methods, a dance action and music beat matching error recognition method based on data mining is designed. The quaternion array is used to represent the joint coordinate points of the dance movement, and the coordinates are rotated to obtain the curve change of the dance movement. The dance movement characteristics are regarded as a set of positive and negative sample data, the initial weights of different sample data are calculated, the absolute value is processed for the music beat signal, the interference factors are filtered with the help of Gauss filter, and according to the rhythm law of the music beat signal, the characteristics of music beat signal are extracted and the feature extraction of dance action matching is completed with music beat. The corresponding relationship between dance action and music beat is regarded as the corresponding model, the pairwise occurrence probability between music beat and action is determined, the matching model between dance action and music beat is discretized, and the peak point of correlation data is introduced to complete the matching between dance action and music beat. The features of matching data are extracted and segmented by short-time Fourier transform, the segmented matching data is transformed into matching data, the matching error identification model is established with the help of support vector mechanism, and the constraint conditions of error detection are set to complete the matching error identification. The experimental results show that the proposed method has high recognition accuracy and high data matching correlation.

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Section: Analysis Of Experimental Resultsmentioning

confidence: 85%

Recognition Method of Matching Error between Dance Action and Music Beat Based on Data Mining

Zhu

2022

Security and Communication Networks

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“…After receiving the spiral CT scan, the patients in the research team need to undergo an image examination, send the relevant two-dimensional images to the base station, and perform image processing procedures. First, in order to prevent the scanned frame from participating in image reconstruction, the area needs to be adjusted [ 10 , 11 ]. Next, construct MPR based on the observation and understanding of the bone window and soft tissue window, remove the tissues that affect the observation, expose the observation area, observe the patient's fracture displacement and fracture line direction, adjust the brightness and contrast appropriately, and save the relevant images.…”

Section: Research Methods Of Imaging Diagnosis Results Of Patients Wi...mentioning

confidence: 99%

The Imaging Diagnosis of Patients with Shoulder Pain Caused by Sports Injury

Dong

Wang

2022

Applied Bionics and Biomechanics

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The shoulder joint is the most complex and movable joint of the human body. A variety of diseases can affect the shoulder joint and cause shoulder pain. Sports injuries are an important and common cause of shoulder pain. In the clinical diagnosis of shoulder joint injury, the most commonly used diagnostic methods are X-ray photography and CT imaging, but X-ray photography has poor ability to distinguish shoulder joints and other tiny tissue structures and has a sense of inspiration for shoulder joint injuries. In addition, CT arthrography has a certain risk to the lesion and is easy to form trauma, and it cannot clearly show the shoulder joint structures such as the rotator cuff and the labrum. Therefore, this article conducts MR imaging diagnostic research on patients with shoulder pain caused by sports injuries and plays an important role in imaging. This article deeply studied the clinical manifestations of shoulder joint pain and image processing technology, designed a research experiment on imaging diagnosis results of patients with shoulder joint pain caused by sports injuries, selected 87 patients with shoulder joint pain in a hospital, and analyzed X-ray photography, CT imaging, and MR imaging diagnosis, three methods to compare the diagnostic accuracy and inspection results and conduct an in-depth analysis of the causes of shoulder joint injury. The experimental results showed that there were 87 patients with shoulder joint pain, 65 patients with rotator cuff tear were diagnosed using arthroscopy, and 63 patients with rotator cuff tear were diagnosed by MR imaging. The accuracy rate was as high as 95.6%. Among them, the proportion caused by sports injuries is the highest, reaching 56%.

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“…The depth image records the distance information from the camera to the surface of the scene object [ 7 ]. The reason why the depth image is also called the distance image is because the change of the pixel value in the depth map corresponds to the change of the distance in the real three-dimensional world, and the real three-dimensional scene can be reflected by the difference in the depth value [ 8 , 9 ]. In the human action recognition based on the depth image, each pixel (x, y) in the depth image represents the distance of each part of the human body from the depth camera plane [ 10 ].…”

Section: Human Feature Recognition Based On Deep Learningmentioning

confidence: 99%

Recognition of Human Body Feature Changes in Sports Health Based on Deep Learning

Jiao

2022

Computational and Mathematical Methods in Medicine

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With the rapid development of social economy and the extensive and in-depth development of national fitness activities, national physical fitness monitoring and research work has achieved rapid development. In recent years, the application of deep learning technology has also achieved research breakthroughs in the field of computer vision. How deep learning technology can effectively capture motion information in sample data and use it to realize the recognition and classification of human actions is currently a research hot spot. Today’s popularization of various shooting devices such as mobile phones and portable action cameras has contributed to the vigorous growth of image data. Therefore, through computer vision technology, image data is widely used in practical application scenarios of human feature recognition. This paper proposes a deep learning network based on the recognition of human body feature changes in sports, improves the recognition method, and compares the recognition accuracy with the original method. The experimental results of this paper show that the result of this paper is 1.68% higher than the original recognition method, the accuracy rate of the improved motion history image is increased by 14.8%, and the overall recognition rate is higher. It can be seen from the above experimental results that this method has achieved good results in human body action recognition.

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VLSI Implementation of a High-Performance Nonlinear Image Scaling Algorithm

Cited by 67 publications

References 36 publications

Recognition Method of Matching Error between Dance Action and Music Beat Based on Data Mining

Recognition Method of Matching Error between Dance Action and Music Beat Based on Data Mining

The Imaging Diagnosis of Patients with Shoulder Pain Caused by Sports Injury

Recognition of Human Body Feature Changes in Sports Health Based on Deep Learning

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