INT3-Horus framework for multispectrum activity interpretation in intelligent environments

Fernández-Caballero, Antonio; Castillo, José Carlos; López, María Teresa; Serrano-Cuerda, Juan; Sokolova, Marina V.

doi:10.1016/j.eswa.2013.06.058

Cited by 20 publications

(13 citation statements)

References 25 publications

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“…Fernández-Caballero [8] presented a state machine-based technique incorporating domain knowledge where motion-based image features are linked to a symbolic notion of hierarchical activity. Successful research focuses on recognising rather simple human activities or patterns [9] even proposing frameworks for monitoring and activity interpretation [10]. These patterns are interesting and related to our proposal in the sense that they involve detections along the time to encode a full activity.…”

Section: Related Workmentioning

confidence: 88%

The Influence of Speed and Position in Dynamic Gesture Recognition for Human-Robot Interaction

et al. 2019

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Human communication relies on several aspects beyond the speech. One of them is gestures as they express intentions, interests, feelings, or ideas and complement the speech. Social robots need to interpret these messages to allow a more natural Human-Robot Interaction. In this sense, our aim is to study the effect of position and speed features in dynamic gesture recognition. We use 3D information to extract the user’s skeleton and calculate the normalized position for all of its joints, and using the temporal variation of such positions, we calculate their speeds. Our three datasets are composed of 1355 samples from 30 users. We consider 14 common gestures in HRI involving upper body movements. A set of classification techniques is evaluated testing these three datasets to find what features perform better. Results indicate that the union of both speed and position achieves the best results among the three possibilities, 0.999 of F-score. The combination that performs better to detect dynamic gestures in real time is finally integrated in our social robot with a simple HRI application to run a proof of concept test to check how the proposal behaves in a realistic scenario.

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Section: Related Workmentioning

confidence: 88%

The Influence of Speed and Position in Dynamic Gesture Recognition for Human-Robot Interaction

et al. 2019

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“…It is important to consider the multisensory approach, which combines multiple sources of information presented by various sensors to generate a more accurate and robust interpretation of the environment [3]. Ultimately, we are talking about semantic interpretation from multi-sensed and video-controlled environments [4], which is the need to recognize situations, activities and interactions between different actors involved [5]. In our case, the goal is to apply smart techniques to the recognition of the activity and mood of older people living alone in their homes [6].…”

Section: Fundamentals Of Smart Emotion Recognition and Regulationmentioning

confidence: 99%

Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation

Fernández-Caballero

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et al. 2014

Ambient Assisted Living and Daily Activities

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Abstract. This paper introduces a project named "Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation". The objective of the project is to find solutions for improving the quality of life and care of the elderly who can or wants to continue living at home by using emotion regulation techniques. Cameras and body sensors are used for monitoring the elderlies' facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people's emotions are inferred and recognized. Music, colour and light are the simulating means to regulate their emotions towards a positive and pleasant mood.

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“…It is important to consider multisensory approaches as well, which combine multiple sources of information presented by various sensors to generate a more accurate and robust interpretation of a given situation (Pavón et al, 2008). Ultimately, a semantic interpretation from multi-sensed and video-controlled environments (Gascueña and Fernández-Caballero, 2011) is required for the recognition of specific situations and activities (Fernández-Caballero et al, 2013). More concretely, our challenge is to apply smart techniques to detect the mood and activity of those living alone in their homes (Bartholmai et al, 2013).…”

Section: Vision Systems To Monitor the Emotional State Of Aging Peoplementioning

confidence: 99%

INT3-Horus framework for multispectrum activity interpretation in intelligent environments

Cited by 20 publications

References 25 publications

The Influence of Speed and Position in Dynamic Gesture Recognition for Human-Robot Interaction

The Influence of Speed and Position in Dynamic Gesture Recognition for Human-Robot Interaction

Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation

A Grand Challenge for Vision Systems: Improving the Quality of Life and Care of Aging Adults

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