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See detailVIEW-INVARIANT ACTION RECOGNITION FROM RGB DATA VIA 3D POSE ESTIMATION
Baptista, Renato UL; Ghorbel, Enjie UL; Papadopoulos, Konstantinos UL et al

in IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK, 12–17 May 2019 (2019, May)

In this paper, we propose a novel view-invariant action recognition method using a single monocular RGB camera. View-invariance remains a very challenging topic in 2D action recognition due to the lack of ... [more ▼]

In this paper, we propose a novel view-invariant action recognition method using a single monocular RGB camera. View-invariance remains a very challenging topic in 2D action recognition due to the lack of 3D information in RGB images. Most successful approaches make use of the concept of knowledge transfer by projecting 3D synthetic data to multiple viewpoints. Instead of relying on knowledge transfer, we propose to augment the RGB data by a third dimension by means of 3D skeleton estimation from 2D images using a CNN-based pose estimator. In order to ensure view-invariance, a pre-processing for alignment is applied followed by data expansion as a way for denoising. Finally, a Long-Short Term Memory (LSTM) architecture is used to model the temporal dependency between skeletons. The proposed network is trained to directly recognize actions from aligned 3D skeletons. The experiments performed on the challenging Northwestern-UCLA dataset show the superiority of our approach as compared to state-of-the-art ones. [less ▲]

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See detailA View-invariant Framework for Fast Skeleton-based Action Recognition Using a Single RGB Camera
Ghorbel, Enjie UL; Papadopoulos, Konstantinos UL; Baptista, Renato UL et al

in 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Prague, 25-27 February 2018 (2019, February)

View-invariant action recognition using a single RGB camera represents a very challenging topic due to the lack of 3D information in RGB images. Lately, the recent advances in deep learning made it ... [more ▼]

View-invariant action recognition using a single RGB camera represents a very challenging topic due to the lack of 3D information in RGB images. Lately, the recent advances in deep learning made it possible to extract a 3D skeleton from a single RGB image. Taking advantage of this impressive progress, we propose a simple framework for fast and view-invariant action recognition using a single RGB camera. The proposed pipeline can be seen as the association of two key steps. The first step is the estimation of a 3D skeleton from a single RGB image using a CNN-based pose estimator such as VNect. The second one aims at computing view-invariant skeleton-based features based on the estimated 3D skeletons. Experiments are conducted on two well-known benchmarks, namely, IXMAS and Northwestern-UCLA datasets. The obtained results prove the validity of our concept, which suggests a new way to address the challenge of RGB-based view-invariant action recognition. [less ▲]

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See detailHome Self-Training: Visual Feedback for Assisting Physical Activity for Stroke Survivors
Baptista, Renato UL; Ghorbel, Enjie UL; Shabayek, Abd El Rahman UL et al

in Computer Methods and Programs in Biomedicine (2019)

Background and Objective: With the increase in the number of stroke survivors, there is an urgent need for designing appropriate home-based rehabilitation tools to reduce health-care costs. The objective ... [more ▼]

Background and Objective: With the increase in the number of stroke survivors, there is an urgent need for designing appropriate home-based rehabilitation tools to reduce health-care costs. The objective is to empower the rehabilitation of post-stroke patients at the comfort of their homes by supporting them while exercising without the physical presence of the therapist. Methods: A novel low-cost home-based training system is introduced. This system is designed as a composition of two linked applications: one for the therapist and another one for the patient. The therapist prescribes personalized exercises remotely, monitors the home-based training and re-adapts the exercises if required. On the other side, the patient loads the prescribed exercises, trains the prescribed exercise while being guided by color-based visual feedback and gets updates about the exercise performance. To achieve that, our system provides three main functionalities, namely: 1) Feedback proposals guiding a personalized exercise session, 2) Posture monitoring optimizing the effectiveness of the session, 3) Assessment of the quality of the motion. Results: The proposed system is evaluated on 10 healthy participants without any previous contact with the system. To analyze the impact of the feedback proposals, we carried out two different experimental sessions: without and with feedback proposals. The obtained results give preliminary assessments about the interest of using such feedback. Conclusions: Obtained results on 10 healthy participants are promising. This encourages to test the system in a realistic clinical context for the rehabilitation of stroke survivors. [less ▲]

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See detailTwo-stage RGB-based Action Detection using Augmented 3D Poses
Papadopoulos, Konstantinos UL; Ghorbel, Enjie UL; Baptista, Renato UL et al

in 18th International Conference on Computer Analysis of Images and Patterns SALERNO, 3-5 SEPTEMBER, 2019 (2019)

In this paper, a novel approach for action detection from RGB sequences is proposed. This concept takes advantage of the recent development of CNNs to estimate 3D human poses from a monocular camera. To ... [more ▼]

In this paper, a novel approach for action detection from RGB sequences is proposed. This concept takes advantage of the recent development of CNNs to estimate 3D human poses from a monocular camera. To show the validity of our method, we propose a 3D skeleton-based two-stage action detection approach. For localizing actions in unsegmented sequences, Relative Joint Position (RJP) and Histogram Of Displacements (HOD) are used as inputs to a k-nearest neighbor binary classifier in order to define action segments. Afterwards, to recognize the localized action proposals, a compact Long Short-Term Memory (LSTM) network with a de-noising expansion unit is employed. Compared to previous RGB-based methods, our approach offers robustness to radial motion, view-invariance and low computational complexity. Results on the Online Action Detection dataset show that our method outperforms earlier RGB-based approaches. [less ▲]

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See detailKey-Skeleton Based Feedback Tool for Assisting Physical Activity
Baptista, Renato UL; Ghorbel, Enjie UL; Shabayek, Abd El Rahman UL et al

in 2018 Zooming Innovation in Consumer Electronics International Conference (ZINC), 30-31 May 2018 (2018, May 31)

This paper presents an intuitive feedback tool able to implicitly guide motion with respect to a reference movement. Such a tool is important in multiple applications requiring assisting physical ... [more ▼]

This paper presents an intuitive feedback tool able to implicitly guide motion with respect to a reference movement. Such a tool is important in multiple applications requiring assisting physical activities as in sports or rehabilitation. Our proposed approach is based on detecting key skeleton frames from a reference sequence of skeletons. The feedback is based on the 3D geometry analysis of the skeletons by taking into account the key-skeletons. Finally, the feedback is illustrated by a color-coded tool, which reflects the motion accuracy. [less ▲]

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See detailAn extension of kernel learning methods using a modified Log-Euclidean distance for fast and accurate skeleton-based Human Action Recognition
Ghorbel, Enjie UL; Boonaert, Jacques; Boutteau, Rémi et al

in Computer Vision and Image Understanding (2018), 175

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See detailKinematic Spline Curves: A temporal invariant descriptor for fast action recognition
Ghorbel, Enjie UL; Boutteau, Rémi; Boonaert, Jacques et al

in Image and Vision Computing (2018), 77

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See detailFeatures and Classification Schemes for View-Invariant and Real-Time Human Action Recognition
Talha, Sid Ahmed Walid; Hammouche, Mounir; Ghorbel, Enjie UL et al

in IEEE Transactions on Cognitive and Developmental Systems (2018), 10(4), 894--902

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See detailFast and accurate human action recognition using RGB-D cameras
Ghorbel, Enjie UL

Doctoral thesis (2017)

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See detailToward a real time view-invariant 3D action recognition
Hammouche, Mounir; Ghorbel, Enjie UL; Fleury, Anthony et al

in International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) (2016)

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See detailA fast and accurate motion descriptor for human action recognition applications
Ghorbel, Enjie UL; Boutteau, Rémi; Bonnaert, Jacques et al

in 2016 23rd International Conference on Pattern Recognition (ICPR) (2016)

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See detailVers une reconnaissance en ligne d'actions à partir de caméras RGB-D
Ghorbel, Enjie UL; Boutteau, Rémi; Boonaert, Jacques et al

in Reconnaissance de Formes et Intelligence Artificielle (2016)

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See detailEvaluation of an anatomically augmented Statistical Shape Model of the scapula: Clinical validation and reliability of landmark selection. Submited to
Borotikar, Bhushan; Ghorbel, Enjie UL; Lempereur, Mathieu et al

in Computer Methods in Biomechanics and Biomedical Engineering. Imaging and Visualization (2015)

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See detailValidation d'un Nouveau Modèle Statistique de Scapula Augmenté de Marqueurs Anatomiques
Borotikar, Bhushan; Ghorbel, Enjie UL; Mutsvangwa, Tinashe et al

in TAIMA 2015: Traitement et Analyse de l'Information: Méthodes et Applications (2015)

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See detail3D real-time human action recognition using a spline interpolation approach
Ghorbel, Enjie UL; Boutteau, Rémi; Boonaert, Jacques et al

in 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA) (2015)

Detailed reference viewed: 21 (0 UL)