TY - GEN
T1 - A Convolutional Neural Network-based Framework for the Assessment of Human Muscles
AU - Ali, Noman
AU - Abubakr, Muhammad
AU - Shaikh, Muhammad Bilal
AU - Shahid, Ali Raza
AU - Poon, Wayne
AU - Qureshi, Rizwan
PY - 2021/11
Y1 - 2021/11
N2 - This paper presents a system for assessing men's physique, using advanced computer vision and deep learning methods. The pipeline involves the segmenting and gauging of the condition of various muscle groups. The proposed system is composed of two different deep learning models working in tandem, the first is an Instance Segmentation Mask R-CNN and the second is GoogLeNet. The Mask R-CNN is used for the accurate multi-class identification and detection of different muscle groups, such as chest, biceps, abs, and shoulders. GoogLeNet then further classifies each muscle group into various levels (level 1, level 2, up to level n). Furthermore, performance metrics, such as accuracy, precision, F1-measure and confusion matrices are used to evaluate the effectiveness of the proposed system. We believe, that as this system provides information regarding the physical shape/ form of a person, it can be used to augment Diet and Exercise Recommendation Systems (DERS) and can have many commercial as well as clinical applications.
AB - This paper presents a system for assessing men's physique, using advanced computer vision and deep learning methods. The pipeline involves the segmenting and gauging of the condition of various muscle groups. The proposed system is composed of two different deep learning models working in tandem, the first is an Instance Segmentation Mask R-CNN and the second is GoogLeNet. The Mask R-CNN is used for the accurate multi-class identification and detection of different muscle groups, such as chest, biceps, abs, and shoulders. GoogLeNet then further classifies each muscle group into various levels (level 1, level 2, up to level n). Furthermore, performance metrics, such as accuracy, precision, F1-measure and confusion matrices are used to evaluate the effectiveness of the proposed system. We believe, that as this system provides information regarding the physical shape/ form of a person, it can be used to augment Diet and Exercise Recommendation Systems (DERS) and can have many commercial as well as clinical applications.
KW - Computer Vision
KW - Deep learning
KW - Muscle assessment
KW - Object detection
KW - RNN
UR - https://www.scopus.com/pages/publications/85125313309
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85125313309&origin=recordpage
U2 - 10.1109/ICCIS54243.2021.9676387
DO - 10.1109/ICCIS54243.2021.9676387
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-1-6654-9442-7
T3 - Proceedings - IEEE International Conference on Computing and Information Sciences, ICCIS
BT - Proceedings - 2021 IEEE 4th International Conference on Computing and Information Sciences
A2 - Jilani, Muhammad Taha
PB - IEEE
T2 - 4th IEEE International Conference on Computing and Information Sciences (IEEE ICCIS 2021)
Y2 - 29 November 2021 through 30 November 2021
ER -