Yoga pose classification: a CNN and MediaPipe inspired deep learning approach for real-world application. J Ambient Intell Human Comput 14, 16551–16562 (2023). https://doi.org/10.1007/s12652-022-03910-0 Download citation Received15 September 2021 Accepted11 May 2022 Published03 June 2022 Issue...
ClassificationSkeletonizationYoga is a centuries-old style of exercise followed by sports personnel, patients, and physiotherapist as their regime. A correct posture and technique are the key points in yoga to reap the maximum benefits. Hence, developing a model to classify yoga postures correctly is...
Yoga pose classification: a CNN and MediaPipe inspired deep learning approach for real-world applicationdoi:10.1007/s12652-022-03910-0Journal of Ambient Intelligence and Humanized Computing - Yoga is a centuries-old style of exercise followed by sports personnel, patients, and physiotherapist as their...
In this paper, we propose a deep-learning model for yoga pose classification, which is the first step of a quality assessment and personalized feedback system. We introduce a wavelet-based model that first takes wavelet transform of input images. The acquired subbands, i.e., ...
Yoga pose annotation and classification by using time-distributed convolutional neural networkdoi:10.11591/ijeecs.v32.i3.pp1639-1647Dhanyal, Somashekhar S.Nandyal, Suvarna S.Indonesian Journal of Electrical Engineering & Computer Science
Classification of yoga pose using machine learning techniques - ScienceDirectJ. PalanimeeraK. Ponmozhi
Yoga is a very well-known practice to curb anxiety and relieve stress and overall wellbeing. There are many yoga poses but the very well-known ones are the downward dog pose, goddess pose, tree pose, plank pose and the warrior pose. Smart technology can be used to classify between them....
Therefore, accurate recognition and classification of yoga poses are of great importance to practitioners.This paper introduces a novel intelligent yoga pose classification system, XcepSENet, which combines the feature extraction capabilities of Mediapipe with an improved Xception model and the SE blocks ...
This study demonstrates that this multimodal technique can be effectively used for yoga pose classification, and possibly for human posture classification, in general. Additionally, CLIP inference time (around 7 ms) supports that the model can be integrated into automated systems for ...
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