Human Action Recognition of Hidden Markov Model Based on Depth Information

التفاصيل البيبلوغرافية
العنوان: Human Action Recognition of Hidden Markov Model Based on Depth Information
المؤلفون: Shaojun Miao, Tongwei Lu, Ling Peng
المصدر: ISPDC
بيانات النشر: IEEE, 2016.
سنة النشر: 2016
مصطلحات موضوعية: 060201 languages & linguistics, Computer science, business.industry, Maximum-entropy Markov model, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Markov process, Pattern recognition, 06 humanities and the arts, 02 engineering and technology, Skeleton (category theory), Markov model, symbols.namesake, Human skeleton, medicine.anatomical_structure, 0602 languages and literature, 0202 electrical engineering, electronic engineering, information engineering, symbols, medicine, 020201 artificial intelligence & image processing, Computer vision, Segmentation, Artificial intelligence, Hidden Markov model, business
الوصف: According to the problem that segmentation method is difficult to get accurate and complete skeleton information, the method of capturing depth image through a depth sensor is proposed which can obtain a complete skeleton information and improve the accuracy of the skeleton key points. First, use depth images to obtain the human skeleton, second, through coordinate transformation to extract the human skeleton, third, take advantage of these features to train the hidden Markov model, last, rely on the hidden Markov model to make behavior recognition. A great number of experiments indicate that the correct recognition rate of this system reaches up to 80%.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::baf30fbab0fffc0487890e4fb62c4c2d
https://doi.org/10.1109/ispdc.2016.58
رقم الأكسشن: edsair.doi...........baf30fbab0fffc0487890e4fb62c4c2d
قاعدة البيانات: OpenAIRE