Real-time Recognition of Yoga Poses using computer Vision for Smart Health Care

• URL: http://arxiv.org/abs/2201.07594v1
• Date: Wed, 19 Jan 2022 13:41:58 GMT
• Title: Real-time Recognition of Yoga Poses using computer Vision for Smart Health Care
• Authors: Abhishek Sharma, Yash Shah, Yash Agrawal, Prateek Jain
• Abstract summary: The work also presents Yoga-hand mudra (hand gestures) identification. The YOGI dataset has been developed which include 10 Yoga postures with around 400-900 images of each pose. XGBoost with RandomSearch CV is most accurate and gives 99.2% accuracy.
• Score: 13.709260905038624
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Nowadays, yoga has become a part of life for many people. Exercises and sports technological assistance is implemented in yoga pose identification. In this work, a self-assistance based yoga posture identification technique is developed, which helps users to perform Yoga with the correction feature in Real-time. The work also presents Yoga-hand mudra (hand gestures) identification. The YOGI dataset has been developed which include 10 Yoga postures with around 400-900 images of each pose and also contain 5 mudras for identification of mudras postures. It contains around 500 images of each mudra. The feature has been extracted by making a skeleton on the body for yoga poses and hand for mudra poses. Two different algorithms have been used for creating a skeleton one for yoga poses and the second for hand mudras. Angles of the joints have been extracted as a features for different machine learning and deep learning models. among all the models XGBoost with RandomSearch CV is most accurate and gives 99.2\% accuracy. The complete design framework is described in the present paper.

Related papers

• Yoga Pose Classification Using Transfer Learning [0.0]
  Yoga-82, a benchmark dataset for large-scale yoga pose recognition with 82 classes, has challenging positions that could make precise annotations impossible. We have used VGG-16, ResNet-50, ResNet-101, and DenseNet-121 and finetuned them in different ways to get better results. The experimental result shows the best performance of DenseNet-121 having the top-1 accuracy of 85% and top-5 accuracy of 96%.
  arXiv  Detail & Related papers  (2024-10-29T14:34:18Z)
• VividPose: Advancing Stable Video Diffusion for Realistic Human Image Animation [79.99551055245071]
  We propose VividPose, an end-to-end pipeline that ensures superior temporal stability. An identity-aware appearance controller integrates additional facial information without compromising other appearance details. A geometry-aware pose controller utilizes both dense rendering maps from SMPL-X and sparse skeleton maps. VividPose exhibits superior generalization capabilities on our proposed in-the-wild dataset.
  arXiv  Detail & Related papers  (2024-05-28T13:18:32Z)
• 3DYoga90: A Hierarchical Video Dataset for Yoga Pose Understanding [0.0]
  3DYoga901 is organized within a three-level label hierarchy. Our dataset includes meticulously curated RGB yoga pose videos and 3D skeleton sequences.
  arXiv  Detail & Related papers  (2023-10-16T07:15:31Z)
• VINECS: Video-based Neural Character Skinning [82.39776643541383]
  We propose a fully automated approach for creating a fully rigged character with pose-dependent skinning weights. We show that our approach outperforms state-of-the-art while not relying on dense 4D scans.
  arXiv  Detail & Related papers  (2023-07-03T08:35:53Z)
• Surya Namaskar: real-time advanced yoga pose recognition and correction for smart healthcare [13.193107713297255]
  Suryanamaskar, also known as salute to the sun, is a yoga practice that combines eight different forms and 12 asanas. Here the Mediapipe Library is used to analyze Surya namaskar situations. Standing is detected in real time with advanced software, as one performs Surya namaskar in front of the camera.
  arXiv  Detail & Related papers  (2022-09-06T13:37:25Z)
• Imposing Temporal Consistency on Deep Monocular Body Shape and Pose Estimation [67.23327074124855]
  This paper presents an elegant solution for the integration of temporal constraints in the fitting process. We derive parameters of a sequence of body models, representing shape and motion of a person, including jaw poses, facial expressions, and finger poses. Our approach enables the derivation of realistic 3D body models from image sequences, including facial expression and articulated hands.
  arXiv  Detail & Related papers  (2022-02-07T11:11:55Z)
• Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency [55.94908688207493]
  We propose a self-supervised framework named SPICE that closes the image quality gap with supervised methods. The key insight enabling self-supervision is to exploit 3D information about the human body in several ways. SPICE achieves state-of-the-art performance on the DeepFashion dataset.
  arXiv  Detail & Related papers  (2021-10-11T17:48:50Z)
• FixMyPose: Pose Correctional Captioning and Retrieval [67.20888060019028]
  We introduce a new captioning dataset named FixMyPose to address automated pose correction systems. We collect descriptions of correcting a "current" pose to look like a "target" pose. To avoid ML biases, we maintain a balance across characters with diverse demographics.
  arXiv  Detail & Related papers  (2021-04-04T21:45:44Z)
• Does Yoga Make You Happy? Analyzing Twitter User Happiness using Textual and Temporal Information [29.89122455417348]
  We investigate the causal relationship between practicing yoga and being happy by incorporating textual and temporal information. Our experiment on Twitter dataset demonstrates that there are 1447 users where "yoga Granger-causes happiness"
  arXiv  Detail & Related papers  (2020-12-05T03:30:49Z)
• Yoga-82: A New Dataset for Fine-grained Classification of Human Poses [46.319423568714505]
  We present a dataset, Yoga-82, for large-scale yoga pose recognition with 82 classes. Yoga-82 consists of complex poses where fine annotations may not be possible. The dataset contains a three-level hierarchy including body positions, variations in body positions, and the actual pose names.
  arXiv  Detail & Related papers  (2020-04-22T01:43:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.