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- Multi-scale lines and edges in V1 and beyond: brightness, object categorization and recognition, and consciousnessPublication . Rodrigues, J. M. F.; du Buf, J. M. H.In this paper we present an improved model for line and edge detection in cortical area V1. This model is based on responses of simple and complex cells, and it is multi-scale with no free parameters. We illustrate the use of the multi-scale line/edge representation in different processes: visual reconstruction or brightness perception, automatic scale selection and object segregation. A two-level object categorization scenario is tested in which pre-categorization is based on coarse scales only and final categorization on coarse plus fine scales. We also present a multi-scale object and face recognition model. Processing schemes are discussed in the framework of a complete cortical architecture. The fact that brightness perception and object recognition may be based on the same symbolic image representation is an indication that the entire (visual) cortex is involved in consciousness.
- Segmentação de imagem em três dimensõesPublication . Rodrigues, J. M. F.; du Buf, J. M. H.
- Artificial intelligence applications and innovations: day-to-day life impactPublication . Rodrigues, João; Cardoso, Pedro; Chinnici, MartaThe idea of an intelligent machine has fascinated humans for centuries. But what is intelligence? Some define it as the capacity for learning, reasoning, understanding or, from a different perspective, the aptitude to grasp truths, relationships, facts, or meanings. All these perspectives require the capacity to acquire data from the surrounding world and, possibly, act over that environment. In short, the building of more or less autonomous agents, served with sensors and actuators, capable of learning and producing educated answers has been long foreseen. New trends in intelligente systems comprise, among other aspects, pervasive robotization, ubiquitous online data access, empowered edge computing, smart spaces, and digital ethics. These trends build the research on “Artificial Intelligence Applications and Innovation”, impacting our day-to-day life, our cities, and even our free time. Nevertheless, artificial intelligence (AI) is still closely associated with some popular misconceptions that cause the public to either have unrealistic fears about it or to have unrealistic expectations about how it will change our workplace and life in general. It is important to show that such fears are unfounded and that new trends, innovations, technologies, and smart systems will be able to improve the way we live, benefiting society without replacing humans in their core activities.
- Mobile five senses augmented reality system: technology acceptance studyPublication . Rodrigues, João; Ramos, Celia; Pereira, Joao A. R.; Sardo, Joao D. P.; Cardoso, PedroThe application of the most recent technologies is fundamental to add value to tourism experiences, as well as in other economic sectors. Mobile Five Senses Augmented Reality (M5SAR) system is a mobile guide instrument for cultural, historical, and museum events. In order to realize the proclaimed five senses, the system has two main modules: a (i) mobile application which deals mainly with the senses of sight and hearing, using for that the mobile device camera to recognize and track on-the-fly (museum's) objects and give related information about them; and a (ii) portable device capable of enhancing the augmented reality (AR) experience to the full five senses through the stimulus of touch, taste, and smell, by associating itself to the users' smartphone or tablet. This paper briefly presents the system's architecture but, the main focus is on the analysis of the users' acceptance for this technology, namely the AR (software) application, and its integration with the (hardware) device to achieve the five senses AR. Results show that social influence, effort expectancy, and facilitating conditions are the key constructs that drive the users to accept and M5SAR's technology.
- BINK: Biological binary keypoint descriptorPublication . Saleiro Filho, Mario; Terzic, Kasim; Rodrigues, João; du Buf, J. M. H.Learning robust keypoint descriptors has become an active research area in the past decade. Matching local features is not only important for computational applications, but may also play an important role in early biological vision for disparity and motion processing. Although there were already some floatingpoint descriptors like SIFT and SURF that can yield high matching rates, the need for better and faster descriptors for real-time applications and embedded devices with low computational power led to the development of binary descriptors, which are usually much faster to compute and to match. Most of these descriptors are based on purely computational methods. The few descriptors that take some inspiration from biological systems are still lagging behind in terms of performance. In this paper, we propose a new biologically inspired binary keypoint descriptor: SINK. Built on responses of cortical V1 cells, it significantly outperforms the other biologically inspired descriptors. The new descriptor can be easily integrated with a V1-based keypoint detector that we previously developed for real-time applications. (C) 2017 Elsevier B.V. All rights reserved.
- Improved line/edge detection and visual reconstructionPublication . Rodrigues, J. M. F.; du Buf, J. M. H.Lines and edges provide important information for object categorization and recognition. In addition, one brightness model is based on a symbolic interpretation of the cortical multi-scale line/edge representation. In this paper we present an improved scheme for line/edge extraction from simple and complex cells and we illustrate the multi-scale representation. This representation can be used for visual reconstruction, but also for nonphotorealistic rendering. Together with keypoints and a new model of disparity estimation, a 3D wireframe representation of e.g. faces can be obtained in the future.
- Luminance, colour, viewpoint and border enhanced disparity energy modelPublication . Martins, Jaime; Rodrigues, Joao; du Buf, J. M. H.The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas.
- A decision-support system to Analyse Customer Satisfaction Applied to a Tourism Transport ServicePublication . Ramos, Celia; Cardoso, Pedro; Fernandes, Hortênsio C. L.; Rodrigues, JoãoDue to the perishable nature of tourist products, which impacts supply and demand, the possibility of analysing the relationship between customers’ satisfaction and service quality can contribute to increased revenues. Machine learning techniques allow the analysis of how these services can be improved or developed and how to reach new markets, and look for the emergence of ideas to innovate and improve interaction with the customer. This paper presents a decision-support system for analysing consumer satisfaction, based on consumer feedback from the customer’s experience when transported by a transfer company, in the present case working in the Algarve region, Portugal. The results show how tourists perceive the service and which factors influence their level of satisfaction and sentiment. One of the results revealed that the first impression associated with good news is what creates the most value in the experience, i.e., “first impressions matter”..
- Minimalistic vision-based cognitive SLAMPublication . Saleiro, Mário; Rodrigues, J. M. F.; du Buf, J. M. H.The interest in cognitive robotics is still increasing, a major goal being to create a system which can adapt to dynamic environments and which can learn from its own experiences. We present a new cognitive SLAM architecture, but one which is minimalistic in terms of sensors and memory. It employs only one camera with pan and tilt control and three memories, without additional sensors nor any odometry. Short-term memory is an egocentric map which holds information at close range at the actual robot position. Long-term memory is used for mapping the environment and registration of encountered objects. Object memory holds features of learned objects which are used as navigation landmarks and task targets. Saliency maps are used to sequentially focus important areas for object and obstacle detection, but also for selecting directions of movements. Reinforcement learning is used to consolidate or enfeeble environmental information in long-term memory. The system is able to achieve complex tasks by executing sequences of visuomotor actions, decisions being taken by goal-detection and goal-completion tasks. Experimental results show that the system is capable of executing tasks like localizing specific objects while building a map, after which it manages to return to the start position even when new obstacles have appeared.
- Fast segmentation of 3D data using an octreePublication . Rodrigues, J. M. F.; Loke, R. E.; du Buf, J. M. H.The algorithm developed uses an octree pyramid in which noise is reduced at the expense of the spatial resolution. At a certain level an unsupervised clustering without spatial connectivity constraints is applied. After the classification, isolated voxels and insignificant regions are removed by assigning them to their neighbours. The spatial resolution is then increased by the downprojection of the regions, level by level. At each level the uncertainty of the boundary voxels is minimised by a dynamic selection and classification of these, using an adaptive 3D filtering. The algorithm is tested using different data sets, including NMR data.