Fitness training driven by image target detection technology
| Autor: | Jinhai Sun, Tuojian Li, Xianliang Zhang, Lei Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Target detection
Biometrics Computer science Training system 0211 other engineering and technologies ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION lcsh:TK7800-8360 02 engineering and technology Fuzzy logic Fcm clustering Histogram Fitness 0202 electrical engineering electronic engineering information engineering Training Segmentation Electrical and Electronic Engineering Cluster analysis 021101 geological & geomatics engineering business.industry lcsh:Electronics 020206 networking & telecommunications Pattern recognition Experimental research Signal Processing Artificial intelligence business Information Systems |
| Zdroj: | EURASIP Journal on Image and Video Processing, Vol 2018, Iss 1, Pp 1-9 (2018) |
| ISSN: | 1687-5281 |
| DOI: | 10.1186/s13640-018-0345-z |
| Popis: | The fitness training system needs to capture the training staff dynamics in real time, but it is difficult to capture the training staff dynamics during the actual training process. Based on this, this study uses the physical characteristics of fitness trainers as indicators for image target detection. According to the human body will dissipate more heat during the fitness process, this study uses infrared capture as the basis of image capture detection technology, uses FCM clustering algorithm as the fuzzy image background segmentation algorithm, and uses k-means clustering analysis to study the gray histogram and propose a composite classification feature tracking method for trainer image tracking. Combined with the experimental research, the research shows that the research method utilizes the advantages of the composite classification feature to improve the detection rate of the human target. Therefore, it is a real-time and very effective infrared image human detection algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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