Abstract
Image quality assessment as perceived by humans is of crucial importance in numerous fields of image processing. Transmission and storage of digital media require efficient methods to reduce the large number of bits to store an image, while maintaining sufficiently high quality compared to the original image. Since subjective evaluations cannot be performed in various scenarios, it is necessary to have objective metrics that predict image quality consistent with human perception. However, objective metrics that considers high levels of the human visual system are still limited. In this paper, we investigate the possibility of automatically predict, based on saliency maps, the minimum image quality threshold from which humans can perceive the elements on a compressed image. We conducted a series of experimental subjective tests where human observers have been exposed to compressed images with decreasing compression rates. To measure the difference between the saliency maps of the compressed and the original image it was used the normalized absolute error metric. Our results indicate that the elements on the image are only perceived by most of the human subjects not at a specific compressed image quality level, but depending on a saliency map difference threshold.

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Abstract
Falling is a very serious problem for our society, as it affects one out of three older adults. Currently, this is a well-known problem and therefore multiple ICT-based solutions for falls management exist. In addition, a small part of them are said to help preventing falls, but most of the reviewed solutions doesn't seem to have their focus in reducing specific fall risk factors like loss of muscle mass or a poor balance. The proposed ICT-based fall prevention solution is based on an existing fall prevention exercise programme specifically designed for the Portuguese population. It takes advantage of the smartphone processing capabilities as well as its built-in inertial sensors to evaluate the movements performed during the execution of specific exercises. Using only a simple smartphone it is possible to provide a friendly and inexpensive solution capable of increasing seniors' adherence to fall prevention exercises as well as raise their motivation to properly execute the exercises in their home environment. © 2013 IEEE.

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Abstract