References of "Antunes, Michel"
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See detailLocalized Trajectories for 2D and 3D Action Recognition
Papadopoulos, Konstantinos UL; Demisse, Girum UL; Ghorbel, Enjie UL et al

in Sensors (2019)

The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion. However, due to noise and background motion ... [more ▼]

The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion. However, due to noise and background motion, many generated trajectories are irrelevant to the actual human activity and can potentially lead to performance degradation. In this paper, we propose Localized Trajectories as an improved version of Dense Trajectories where motion trajectories are clustered around human body joints provided by RGB-D cameras and then encoded by local Bag-of-Words. As a result, the Localized Trajectories concept provides an advanced discriminative representation of actions. Moreover, we generalize Localized Trajectories to 3D by using the depth modality. One of the main advantages of 3D Localized Trajectories is that they describe radial displacements that are perpendicular to the image plane. Extensive experiments and analysis were carried out on five different datasets. [less ▲]

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See detailAnticipating Suspicious Actions using a Small Dataset of Action Templates
Baptista, Renato UL; Antunes, Michel; Aouada, Djamila UL et al

in 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) (2018, January)

In this paper, we propose to detect an action as soon as possible and ideally before it is fully completed. The objective is to support the monitoring of surveillance videos for preventing criminal or ... [more ▼]

In this paper, we propose to detect an action as soon as possible and ideally before it is fully completed. The objective is to support the monitoring of surveillance videos for preventing criminal or terrorist attacks. For such a scenario, it is of importance to have not only high detection and recognition rates but also low time latency for the detection. Our solution consists in an adaptive sliding window approach in an online manner, which efficiently rejects irrelevant data. Furthermore, we exploit both spatial and temporal information by constructing feature vectors based on temporal blocks. For an added efficiency, only partial template actions are considered for the detection. The relationship between the template size and latency is experimentally evaluated. We show promising preliminary experimental results using Motion Capture data with a skeleton representation of the human body. [less ▲]

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See detailA Revisit of Action Detection using Improved Trajectories
Papadopoulos, Konstantinos UL; Antunes, Michel; Aouada, Djamila UL et al

in IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Alberta, Canada, 15–20 April 2018 (2018)

In this paper, we revisit trajectory-based action detection in a potent and non-uniform way. Improved trajectories have been proven to be an effective model for motion description in action recognition ... [more ▼]

In this paper, we revisit trajectory-based action detection in a potent and non-uniform way. Improved trajectories have been proven to be an effective model for motion description in action recognition. In temporal action localization, however, this approach is not efficiently exploited. Trajectory features extracted from uniform video segments result in significant performance degradation due to two reasons: (a) during uniform segmentation, a significant amount of noise is often added to the main action and (b) partial actions can have negative impact in classifier's performance. Since uniform video segmentation seems to be insufficient for this task, we propose a two-step supervised non-uniform segmentation, performed in an online manner. Action proposals are generated using either 2D or 3D data, therefore action classification can be directly performed on them using the standard improved trajectories approach. We experimentally compare our method with other approaches and we show improved performance on a challenging online action detection dataset. [less ▲]

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See detailFlexible Feedback System for Posture Monitoring and Correction
Baptista, Renato UL; Antunes, Michel; Shabayek, Abd El Rahman UL et al

in IEEE International Conference on Image Information Processing (ICIIP) (2017)

In this paper, we propose a framework for guiding patients and/or users in how to correct their posture in real-time without requiring a physical or a direct intervention of a therapist or a sports ... [more ▼]

In this paper, we propose a framework for guiding patients and/or users in how to correct their posture in real-time without requiring a physical or a direct intervention of a therapist or a sports specialist. In order to support posture monitoring and correction, this paper presents a flexible system that continuously evaluates postural defects of the user. In case deviations from a correct posture are identified, then feedback information is provided in order to guide the user to converge to an appropriate and stable body condition. The core of the proposed approach is the analysis of the motion required for aligning body-parts with respect to postural constraints and pre-specified template skeleton poses. Experimental results in two scenarios (sitting and weight lifting) show the potential of the proposed framework. [less ▲]

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See detailSTARR - Decision SupporT and self-mAnagement system for stRoke survivoRs Vision based Rehabilitation System
Shabayek, Abd El Rahman UL; Baptista, Renato UL; Papadopoulos, Konstantinos UL et al

in European Project Space on Networks, Systems and Technologies (2017)

This chapter explains a vision based platform developed within a European project on decision support and self-management for stroke survivors. The objective is to provide a low cost home rehabilitation ... [more ▼]

This chapter explains a vision based platform developed within a European project on decision support and self-management for stroke survivors. The objective is to provide a low cost home rehabilitation system. Our main concern is to maintain the patients' physical activity while carrying a continuous monitoring of his physical and emotional state. This is essential for recovering some autonomy in daily life activities and preventing a second damaging stroke. Post-stroke patients are initially subject to physical therapy under the supervision of a health professional to follow up on their daily physical activity and monitor their emotional state. However, due to social and economical constraints, home based rehabilitation is eventually suggested. Our vision platform paves the way towards having low cost home rehabilitation. [less ▲]

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