Développement d’un système de vérification de la prière à base de deep learning
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Date
2023-06-06
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
university of eloued جامعة الوادي
Abstract
Ab ¤ ¨¡¤ , Ab` ¨ ¢l ¢ r § A ¤ Ah ± Ty A T Ak ®O ®F³ ` dq
As ³ r Ð Yl r ¥ ¨t w` d§d` An¡ F° . lsm Ahyl FA §
Yl AblF r ¥§ @¡ Amm.( wn Tl ¤ Ah ³A, T w yK ,ry A¡z : ) Ysn§ ¢l` ¤
Aynq d ts§ ¨ Ð A\ rt A wmth , m` @¡ ¨ .®Ol y O º ±
r tF A\n l`t§ § .®O sls T } q tl ¨ AnW}¯ ºA @
d tFA Ð yq t§ .¨l`f
w ¨ Tmhm º Tysy¶r AR¤±
y A§dy d tFA Ahyl wO ¨t Tysy¶r ªAqn zym AfWtq
¨ , ¨ µ d A`J , Ty¶wK T A ) nO d tFA T r tsm A Ayb T A`
.( 16 Ty¶rm TFdnh T wm m, CA
r
®O Ay`Rw sls Yl ©wt Ty` r Tm¶A d tFA ¶Atn q t ¾ry ¤
Yl Anys ºr kmm k ¤ , T§A l T` K Ahyl wO ¨t ¶Atn .Islam has given prayer a high status because it is the first thing God has commanded in
matters of worship, and it is the first worship for which a Muslim is held accountable.
Unfortunately, there are many factors that affect human memory and make it forget(Ex:
Alzheimer’s, aging, stress and lack of sleep). This negatively affects the correct
performance of the prayer. In this work, we are interested in proposing an intelligent
system that uses AI techniques in order to verify the validity of the prayer sequence.
The system must learn to extract key poses (tracking) in order to perform the task
in real time. This is achieved by using posture Information extracted from features
from key points obtained using mediapipe. Instead of general features of distances
and angles, geometric moments of posture is used as features for pose classification
and then processed the extracted data with a classifier(Random Forest, SVM, KNN,
VGG16).Finally, we check the results with a reference prayer sequence. The obtained
Description
mémoire master informatuque
Keywords
. y A§dy , ¨ µ l`t , ym` l`t , ®O , prayer, Deep-learning, Machine learning, mediapipe.