Episodic Reasoning for Vision-Based Human Action Recognition

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning

Perspective Chapter: A Conceptualization of Measuring People’s Activity in Sustaining Urban Life

The criterion of human activity could be one of the critical points in dealing with street life mainly and urban vitality frequently. An attempt to classify the distinct patterns of activities is recently required. The potentiality of a street is to formulate people’s interaction and responses to the street edges and reactions to each other. This chapter highlights the more significant outline regarding human activities and their patterns, besides their classifications. In this regard, the chapter aims to create a conceptual framework to form a platform for analyzing and studying the effectiveness of street life at the micro level. In this chapter, a research type is a descriptive-analytical approach; regarding the method, it employs a broad spectrum of related literature reviews. Consequently, the street edge generates the three main (and their oppositional) human activities. These activities can be categorized as necessary versus optional, individual against social, and staying as opposed to moving. Increasing the calls toward the sustainability of urban livability and street life versus decreasing the motor-based street has become a more significant demand. The street is a vital milieu that offers different opportunities for those who present and use such urban space as the street

Inteligencia computacional en sistemas de teleasistencia en domicilios

156 p.Este trabajo presenta un sistema inteligente de predicción del comportamiento de cara a prevenir situaciones de riesgo en el hogar, y que está orientado principalmente orientado a personas mayores. El sistema presenta una modelo híbrido basado en Reglas Heurísticas introducidas por expertos en el dominio, y un Módulo de Detección Automática de Patrones, conformado por un sistema combinado de clasificadores basados en técnicas de Inteligencia Artificial. El sistema ha sido probado en entornos reales y productivos en diversos domicilios. Para lograrlo, el sistema utiliza por un lado la información de sensores simples en el hogar, por otro el conocimiento de sus actividades físicas recopiladas por aplicaciones móviles y por último la información de salud personalizada basada en informes clínicos codificados en el sistema. Actualmente, se está implantando en condiciones reales, con una precisión superior al 81%

Inteligencia computacional en sistemas de teleasistencia en domicilios

156 p.Este trabajo presenta un sistema inteligente de predicción del comportamiento de cara a prevenir situaciones de riesgo en el hogar, y que está orientado principalmente orientado a personas mayores. El sistema presenta una modelo híbrido basado en Reglas Heurísticas introducidas por expertos en el dominio, y un Módulo de Detección Automática de Patrones, conformado por un sistema combinado de clasificadores basados en técnicas de Inteligencia Artificial. El sistema ha sido probado en entornos reales y productivos en diversos domicilios. Para lograrlo, el sistema utiliza por un lado la información de sensores simples en el hogar, por otro el conocimiento de sus actividades físicas recopiladas por aplicaciones móviles y por último la información de salud personalizada basada en informes clínicos codificados en el sistema. Actualmente, se está implantando en condiciones reales, con una precisión superior al 81%

Challenges of human behavior understanding

Recent advances in pattern recognition has allowed computer scientists and psychologists to jointly address automatic analysis of of human behavior via computers. The Workshop on Human Behavior Understanding at the International Conference on Pattern Recognition explores a number of different aspects and open questions in this field, and demonstrates the multi-disciplinary nature of this research area. In this brief summary, we give an overview of the Workshop and discuss the main research challenges