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Mr. Israr Akhter
Air University

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0 Computer Vision
0 Cryptography
0 Image Processing
0 Information Security
0 machine leaning

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Journal article
Published: 28 February 2021 in Remote Sensing
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Advances in video capturing devices enable adaptive posture estimation (APE) and event classification of multiple human-based videos for smart systems. Accurate event classification and adaptive posture estimation are still challenging domains, although researchers work hard to find solutions. In this research article, we propose a novel method to classify stochastic remote sensing events and to perform adaptive posture estimation. We performed human silhouette extraction using the Gaussian Mixture Model (GMM) and saliency map. After that, we performed human body part detection and used a unified pseudo-2D stick model for adaptive posture estimation. Multifused data that include energy, 3D Cartesian view, angular geometric, skeleton zigzag and moveable body parts were applied. Using a charged system search, we optimized our feature vector and deep belief network. We classified complex events, which were performed over sports videos in the wild (SVW), Olympic sports, UCF aerial action dataset and UT-interaction datasets. The mean accuracy of human body part detection was 83.57% over the UT-interaction, 83.00% for the Olympic sports and 83.78% for the SVW dataset. The mean event classification accuracy was 91.67% over the UT-interaction, 92.50% for Olympic sports and 89.47% for SVW dataset. These results are superior compared to existing state-of-the-art methods.

ACS Style

Munkhjargal Gochoo; Israr Akhter; Ahmad Jalal; KiBum Kim. Stochastic Remote Sensing Event Classification over Adaptive Posture Estimation via Multifused Data and Deep Belief Network. Remote Sensing 2021, 13, 912 .

AMA Style

Munkhjargal Gochoo, Israr Akhter, Ahmad Jalal, KiBum Kim. Stochastic Remote Sensing Event Classification over Adaptive Posture Estimation via Multifused Data and Deep Belief Network. Remote Sensing. 2021; 13 (5):912.

Chicago/Turabian Style

Munkhjargal Gochoo; Israr Akhter; Ahmad Jalal; KiBum Kim. 2021. "Stochastic Remote Sensing Event Classification over Adaptive Posture Estimation via Multifused Data and Deep Belief Network." Remote Sensing 13, no. 5: 912.

Journal article
Published: 24 November 2020 in Sustainability
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This paper suggests that human pose estimation (HPE) and sustainable event classification (SEC) require an advanced human skeleton and context-aware features extraction approach along with machine learning classification methods to recognize daily events precisely. Over the last few decades, researchers have found new mechanisms to make HPE and SEC applicable in daily human life-log events such as sports, surveillance systems, human monitoring systems, and in the education sector. In this research article, we propose a novel HPE and SEC system for which we designed a pseudo-2D stick model. To extract full-body human silhouette features, we proposed various features such as energy, sine, distinct body parts movements, and a 3D Cartesian view of smoothing gradients features. Features extracted to represent human key posture points include rich 2D appearance, angular point, and multi-point autocorrelation. After the extraction of key points, we applied a hierarchical classification and optimization model via ray optimization and a K-ary tree hashing algorithm over a UCF50 dataset, an hmdb51 dataset, and an Olympic sports dataset. Human body key points detection accuracy for the UCF50 dataset was 80.9%, for the hmdb51 dataset it was 82.1%, and for the Olympic sports dataset it was 81.7%. Event classification for the UCF50 dataset was 90.48%, for the hmdb51 dataset it was 89.21%, and for the Olympic sports dataset it was 90.83%. These results indicate better performance for our approach compared to other state-of-the-art methods.

ACS Style

Ahmad Jalal; Israr Akhtar; KiBum Kim. Human Posture Estimation and Sustainable Events Classification via Pseudo-2D Stick Model and K-ary Tree Hashing. Sustainability 2020, 12, 9814 .

AMA Style

Ahmad Jalal, Israr Akhtar, KiBum Kim. Human Posture Estimation and Sustainable Events Classification via Pseudo-2D Stick Model and K-ary Tree Hashing. Sustainability. 2020; 12 (23):9814.

Chicago/Turabian Style

Ahmad Jalal; Israr Akhtar; KiBum Kim. 2020. "Human Posture Estimation and Sustainable Events Classification via Pseudo-2D Stick Model and K-ary Tree Hashing." Sustainability 12, no. 23: 9814.

Conference paper
Published: 21 December 2018 in Proceedings of the 4th international conference on knowledge and innovation in Engineering, Science and Technology
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ACS Style

M. Attique Ur Rehman; Hasan Raza; Israr Akhter. SECURITY ENHANCEMENT OF HILL CIPHER BY USING NON-SQUARE MATRIX APPROACH. Proceedings of the 4th international conference on knowledge and innovation in Engineering, Science and Technology 2018, 1 .

AMA Style

M. Attique Ur Rehman, Hasan Raza, Israr Akhter. SECURITY ENHANCEMENT OF HILL CIPHER BY USING NON-SQUARE MATRIX APPROACH. Proceedings of the 4th international conference on knowledge and innovation in Engineering, Science and Technology. 2018; ():1.

Chicago/Turabian Style

M. Attique Ur Rehman; Hasan Raza; Israr Akhter. 2018. "SECURITY ENHANCEMENT OF HILL CIPHER BY USING NON-SQUARE MATRIX APPROACH." Proceedings of the 4th international conference on knowledge and innovation in Engineering, Science and Technology , no. : 1.