Robust human detection through fusion of color and infrared video

This PhD thesis develops and implements a robust multisensor human detection system based on fusing the information provided after segmenting infrared and color videos

Lateral inhibition in accumulative computation and fuzzy sets for human fall pattern recognition in colour and infrared imagery

Fall detection is an emergent problem in pattern recognition. In this paper, a novel approach which enables to identify a type of a fall and reconstruct its characteristics is presented. The features detected include the position previous to a fall, the direction and velocity of a fall, and the postfall inactivity. Video sequences containing a possible fall are analysed image by image using the lateral inhibition in accumulative computation method.With this aim, the region of interest of human figures is examined in each image, and geometrical and kinematic characteristics for the sequence are calculated.The approach is valid in colour and in infrared video

Lateral Inhibition in Accumulative Computation and Fuzzy Sets for Human Fall Pattern Recognition in Colour and Infrared Imagery

Fall detection is an emergent problem in pattern recognition. In this paper, a novel approach which enables to identify a type of a fall and reconstruct its characteristics is presented. The features detected include the position previous to a fall, the direction and velocity of a fall, and the postfall inactivity. Video sequences containing a possible fall are analysed image by image using the lateral inhibition in accumulative computation method. With this aim, the region of interest of human figures is examined in each image, and geometrical and kinematic characteristics for the sequence are calculated. The approach is valid in colour and in infrared video

Robust people segmentation by static infrared surveillance camera

In this paper, a new approach to real-time people segmentation through processing images captured by an infrared camera is introduced. The approach starts detecting human candidate blobs processed through traditional image thresholding techniques. Afterwards, the blobs are refined with the objective of validating the content of each blob. The question to be solved is if each blob contains one single human candidate or more than one. If the blob contains more than one possible human, the blob is divided to fit each new candidate in height and width

A multi-modal approach for activity classification and fall detection

"Special issue : Intelligent multisensory systems in support of information society"The society is changing towards a new paradigm in which an increasing number of old adults live alone. In parallel, the incidence of conditions that affect mobility and independence is also rising as a consequence of a longer life expectancy. In this paper, the specific problem of falls of old adults is addressed by devising a technological solution for monitoring these users. Video cameras, accelerometers and GPS sensors are combined in a multi-modal approach to monitor humans inside and outside the domestic environment. Machine learning techniques are used to detect falls and classify activities from accelerometer data. Video feeds and GPS are used to provide location inside and outside the domestic environment. It results in a monitoring solution that does not imply the confinement of the users to a closed environment.This work is funded by National Funds through the FCT-Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst- OE/EEI/UI0752/2011. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009). This work is also partially supported by the Spanish Ministerio de Economía y Competitividad / FEDER under project TIN2010-20845-C03-01

Defining a strategy to perform life-tests with analog devices

Unlike for memory elements inside integrated circuits, scarce life tests have been performed to study single event transients in discrete analog devices. The reason is that life tests require a large amount of samples to be stored for having enough data allowing statistical conclusions and, usually, single event transients are captured by means of oscilloscopes. In this paper, we propose a strategy to carry out life tests in analog voltage comparators by means of digital programmable device that can detect anomalous pulses in the voltage comparator. Besides, the idea on which this kind of tests relies can be extended to be used with other families of analog devices, such as operational amplifiers, voltage references, etc

Segmenting humans from mobile thermal infrared imagery

Perceiving the environment is crucial in any application related to mobile robotics research. In this paper, a new approach to real-time human detection through processing video captured by a thermal infrared camera mounted on the indoor autonomous mobile platform mSecurit TM is introduced. The approach starts with a phase of static analysis for the detection of human candidates through some classical image processing techniques such as image normalization and thresholding. Then, the proposal uses Lukas and Kanade optical flow without pyramids algorithm for filtering moving foreground objects from moving scene background. The results of both phases are compared to enhance the human segmentation by infrared camera. Indeed, optical flow will emphasize the foreground moving areas gotten at the initial human candidates detection

Low Latency Estimation of Motor Intentions to Assist Reaching Movements along Multiple Sessions in Chronic Stroke Patients: A Feasibility Study

A corrigendum on Low Latency Estimation of Motor Intentions to Assist Reaching Movements along Multiple Sessions in Chronic Stroke Patients: A Feasibility Study by Ibáñez, J., Monge-Pereira, E., Molina-Rueda, F., Serrano, J. I., del Castillo, M. D., Cuesta-Gómez, A., et al. (2017). Front. Neurosci. 11:126. doi: 10.3389/fnins.2017.00126. In the recently published article, there were incorrect and missing contents in the Acknowledgments section

La adaptación de materiales docentes de marketing para estudiantes con necesidades especiales. Proyecto Speaking Library

Este trabajo presenta la experiencia docente de una Red multidisciplinar de investigadores (Red I+Do+i), en la que han participado profesorado y estudiantes. El objetivo principal de la experiencia docente “Speaking Library” es tiene una doble vertiente. Por un lado, generar documentos de trabajo especializados en investigación en docencia y en materias curriculares relevantes para el alumnado, así como en soportes más accesibles, atractivos y útiles para la comunidad educativa. Se ha tenido especial interés en los estudiantes con Necesidades Específicas de Apoyo Educativo (NEAE) y en este sentido la creación de materiales ha sido fundamentalmente audiovisual. Por otro lado, la gestión dichos materiales a través de repositorios universitarios (Universidad de Alicante y Universidad Miguel Hernández) y de un canal docente de YouTube (canal IDOi), para su ulterior difusión nacional e internacional a las distintas bases de datos y portales adecuados (OCW, blogs UA, VUALA, Blogs externos, etc.) que facilitarán su consulta. Los resultados y reflexiones finales presentan varios documentos convertidos a un formato amigable, visual y valioso para los estudiantes con NEAE, a la vez que se ha diseñado un protocolo de actuación para la elaboración de los mismos y creado un canal docente en YouTube

Robust human detection through fusion of color and infrared video

Advisors: Antonio Fernandez-Caballero and María T. Lopez. Date and location of PhD thesis defense: 16 December 2013, Universidad de Castilla-La ManchaThis PhD thesis develops and implements a robust multisensor human detection system based on fusing the information provided after segmenting infrared and color videos