970 research outputs found
Custom Integrated Circuits
Contains reports on twelve research projects.Analog Devices, Inc.International Business Machines, Inc.Joint Services Electronics Program (Contract DAAL03-86-K-0002)Joint Services Electronics Program (Contract DAAL03-89-C-0001)U.S. Air Force - Office of Scientific Research (Grant AFOSR 86-0164)Rockwell International CorporationOKI Semiconductor, Inc.U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)Charles Stark Draper LaboratoryNational Science Foundation (Grant MIP 84-07285)National Science Foundation (Grant MIP 87-14969)Battelle LaboratoriesNational Science Foundation (Grant MIP 88-14612)DuPont CorporationDefense Advanced Research Projects Agency/U.S. Navy - Office of Naval Research (Contract N00014-87-K-0825)American Telephone and TelegraphDigital Equipment CorporationNational Science Foundation (Grant MIP-88-58764
Understanding Physiological and Degenerative Natural Vision Mechanisms to Define Contrast and Contour Operators
BACKGROUND:Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. METHODOLOGY:First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. CONCLUSIONS:We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery
A historical perspective of algorithmic lateral inhibition and accumulative computation in computer vision
Certainly, one of the prominent ideas of Professor José Mira was that it is absolutely mandatory to specify the mechanisms and/or processes underlying each task and inference mentioned in an architecture in order to make operational that architecture. The conjecture of the last fifteen years of joint research has been that any bottom-up organization may be made operational using two biologically inspired methods called ?algorithmic lateral inhibition?, a generalization of lateral inhibition anatomical circuits, and ?accumulative computation?, a working memory related to the temporal evolution of the membrane potential. This paper is dedicated to the computational formulation of both methods. Finally, all of the works of our group related to this methodological approximation are mentioned and summarized, showing that all of them support the validity of this approximation
Towards a semi-automatic situation diagnosis system in surveillance tasks
This paper describes an ongoing project that develops a set of generic components to help humans (semi-automatic system) in surveillance and security tasks in several scenarios. These components are based in the computational model of a set of selective and Active VISual Attention mechanisms with learning capacity (AVISA) and in the superposition of an ?intelligence? layer that incorporates the knowledge of human experts in security tasks. The project described integrates the responses of these alert mechanisms in the synthesis of the three basic subtasks present in any surveillance and security activity: real-time monitoring, situation diagnosing, and action planning and control. In order to augment the diversity of environments and situations where AVISA system may be used, as well as its efficiency as support to surveillance tasks, knowledge components derived from situating cameras on mobile platforms are also developed
A conceptual frame with two neural mechanisms to model selective visual attention processes
An important problem in artificial intelligence (AI) is to find calculation procedures to save the semantic gap between the analytic formulations of the neuronal models and the concepts of the natural language used to describe the cognitive processes. In this work we explore a way of saving this gap for the case of the attentional processes, consisting in (1) proposing in first place a conceptual model of the attention double bottom-up/top-down organization, (2) proposing afterwards a neurophysiological model of the cortical and sub-cortical involved structures, (3) establishing the correspondences between the entities of (1) and (2), (4) operationalizing the model by using biologically inspired calculation mechanisms (algorithmic lateral inhibition and accumulative computation) formulated at symbolic level, and, (5) assessing the validity of the proposal by accommodating the works of the research team on diverse aspects of attention associated to visual surveillance tasks. The results obtained support in a reasonable way the validity of the proposal and enable its application in surveillance tasks different from the ones considered in this work. In particular, this is the case when linking the geometric descriptions of a scene with the corresponding activity level
Custom Integrated Circuits
Contains reports on nine research projects.Analog Devices, Inc.International Business Machines CorporationJoint Services Electronics Program Contract DAAL03-89-C-0001U.S. Air Force - Office of Scientific Research Contract AFOSR 86-0164BDuPont CorporationNational Science Foundation Grant MIP 88-14612U.S. Navy - Office of Naval Research Contract N00014-87-K-0825American Telephone and TelegraphDigital Equipment CorporationNational Science Foundation Grant MIP 88-5876
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
Gravitational Models Explain Shifts on Human Visual Attention
Visual attention refers to the human brain's ability to select relevant
sensory information for preferential processing, improving performance in
visual and cognitive tasks. It proceeds in two phases. One in which visual
feature maps are acquired and processed in parallel. Another where the
information from these maps is merged in order to select a single location to
be attended for further and more complex computations and reasoning. Its
computational description is challenging, especially if the temporal dynamics
of the process are taken into account. Numerous methods to estimate saliency
have been proposed in the last three decades. They achieve almost perfect
performance in estimating saliency at the pixel level, but the way they
generate shifts in visual attention fully depends on winner-take-all (WTA)
circuitry. WTA is implemented} by the biological hardware in order to select a
location with maximum saliency, towards which to direct overt attention. In
this paper we propose a gravitational model (GRAV) to describe the attentional
shifts. Every single feature acts as an attractor and {the shifts are the
result of the joint effects of the attractors. In the current framework, the
assumption of a single, centralized saliency map is no longer necessary, though
still plausible. Quantitative results on two large image datasets show that
this model predicts shifts more accurately than winner-take-all
East-West Paths to Unconventional Computing
Unconventional computing is about breaking boundaries in thinking, acting and computing. Typical topics of this non-typical field include, but are not limited to physics of computation, non-classical logics, new complexity measures, novel hardware, mechanical, chemical and quantum computing. Unconventional computing encourages a new style of thinking while practical applications are obtained from uncovering and exploiting principles and mechanisms of information processing in and functional properties of, physical, chemical and living systems; in particular, efficient algorithms are developed, (almost) optimal architectures are designed and working prototypes of future computing devices are manufactured. This article includes idiosyncratic accounts of ‘unconventional computing’ scientists reflecting on their personal experiences, what attracted them to the field, their inspirations and discoveries.info:eu-repo/semantics/publishedVersio
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