Download or read book A Neural Model Combining Attentional Orienting to Object Recognition Preliminary Explorations on the Interplay Between Where and What written by and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a model of primate vision that integrates both an attentional orienting ("where") pathway and an object recognition ("what") pathway. The fast visual attention front-end rapidly selects the few most conspicuous image locations, and the slower object recognition back-end identifies objects at the selected locations. The model is applied to classical visual search tasks, consisting of finding a specific target among an array of distracting visual patterns (e.g., a circle among many squares). The encouraging results obtained, in which substantial speedup is achieved by the combined attention- recognition model while maintaining good recognition performance compared to an exhaustive search, suggest that the biologically-inspired architecture proposed represents an efficient solution to the difficult problem of rapid scene analysis.

Download or read book Artificial Neural Networks ICANN 2002 written by Jose R. Dorronsoro and published by Springer. This book was released on 2003-08-03 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conferences on Arti?cial Neural Networks, ICANN, have been held annually since 1991 and over the years have become the major European meeting in neural networks. This proceedings volume contains all the papers presented at ICANN 2002, the 12th ICANN conference, held in August 28– 30, 2002 at the Escuela T ́ecnica Superior de Inform ́atica of the Universidad Aut ́onoma de Madrid and organized by its Neural Networks group. ICANN 2002 received a very high number of contributions, more than 450. Almost all papers were revised by three independent reviewers, selected among the more than 240 serving at this year’s ICANN, and 221 papers were ?nally selected for publication in these proceedings (due to space considerations, quite a few good contributions had to be left out). I would like to thank the Program Committee and all the reviewers for the great collective e?ort and for helping us to have a high quality conference.

Download or read book VOCUS A Visual Attention System for Object Detection and Goal Directed Search written by Simone Frintrop and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents a complete computational system for visual attention and object detection. VOCUS (Visual Object detection with a Computational attention System) represents a major step forward on integrating data-driven and model-driven information into a single framework. Additionally, the volume contains an extensive review of the literature on visual attention, detailed evaluations of VOCUS in different settings, and applications of the system.

Download or read book Models of Visual Attention Using Computational Cognitive Neuroscience in Machine Vision written by Manjunath R Kounte and published by Lulu Publication. This book was released on 2021-04-28 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vision is the most important of the five human senses, since it provides over 85% of the information our brain receives from the external world. Its main goal is to interpret and to interact with the environments we are living in. In everyday life, humans are capable of perceiving thousands of objects, identifying hundreds of faces, recognizing numerous traffic signs, and appreciating beauty effortlessly. The ease with which humans achieve these tasks is in no way due to the simplicity of the tasks but is a proof of the high degree of development of our vision system.

Download or read book Biologically Motivated Computer Vision written by Heinrich H. Bülthoff and published by Springer. This book was released on 2003-08-02 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Biologically Motivated Computer Vision, BMCV 2002, held in Tübingen, Germany, in November 2002. The 22 revised full papers and 37 revised short papers presented together with 6 invited papers were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on neurons and features, motion, mid-level vision, recognition - from scenes to neurons, attention, robotics, and cognitive vision.

Download or read book Recent Trends in Materials and Mechanical Engineering Materials Mechatronics and Automation written by Qi Luo and published by Trans Tech Publications Ltd. This book was released on 2011-05-03 with total page 2400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume is indexed by Thomson Reuters CPCI-S (WoS). This collection of over 429 peer-reviewed papers on Materials and Mechanical Engineering is divided into the chapters: 1: Materials Engineering and Mechanical Engineering - 2: Manufacturing and Production Processes - 3: Automotive Engineering and Industry Application. It provides an authoritative overview of the subject.

Download or read book Object Recognition Attention and Action written by Naoyuki Osaka and published by Springer Science & Business Media. This book was released on 2009-03-12 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human object recognition is a classical topic both for philosophy and for the natural sciences. Ultimately, understanding of object recognition will be promoted by the cooperation of behavioral research, neurophysiology, and computation. This original book provides an excellent introduction to the issues that are involved. It contains chapters that address the ways in which humans and machines attend to, recognize, and act toward objects in the visual environment.

Download or read book Attentional Selection for Object Recognition A Gentle Way written by and published by . This book was released on 2002 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Attentional selection of an object for recognition is often modeled using all-or-nothing switching of neuronal connection pathways from the attended region of the retinal input to the recognition units. However, there is little physiological evidence for such all-or-none modulation in early areas. We present a combined model for spatial attention and object recognition in which the recognition system monitors the entire visual field, but attentional modulation by as little as 20% at a high level is sufficient to recognize multiple objects. To determine the size and shape of the region to be modulated, a rough segmentation is performed, based on pre-attentive features already computed to guide attention. Testing with synthetic and natural stimuli demonstrates that our new approach to attentional selection for recognition yields encouraging results in addition to being biologically plausible.

Download or read book How Humans Recognize Objects Segmentation Categorization and Individual Identification written by Chris Fields and published by Frontiers Media SA. This book was released on 2016-08-18 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human beings experience a world of objects: bounded entities that occupy space and persist through time. Our actions are directed toward objects, and our language describes objects. We categorize objects into kinds that have different typical properties and behaviors. We regard some kinds of objects – each other, for example – as animate agents capable of independent experience and action, while we regard other kinds of objects as inert. We re-identify objects, immediately and without conscious deliberation, after days or even years of non-observation, and often following changes in the features, locations, or contexts of the objects being re-identified. Comparative, developmental and adult observations using a variety of approaches and methods have yielded a detailed understanding of object detection and recognition by the visual system and an advancing understanding of haptic and auditory information processing. Many fundamental questions, however, remain unanswered. What, for example, physically constitutes an “object”? How do specific, classically-characterizable object boundaries emerge from the physical dynamics described by quantum theory, and can this emergence process be described independently of any assumptions regarding the perceptual capabilities of observers? How are visual motion and feature information combined to create object information? How are the object trajectories that indicate persistence to human observers implemented, and how are these trajectory representations bound to feature representations? How, for example, are point-light walkers recognized as single objects? How are conflicts between trajectory-driven and feature-driven identifications of objects resolved, for example in multiple-object tracking situations? Are there separate “what” and “where” processing streams for haptic and auditory perception? Are there haptic and/or auditory equivalents of the visual object file? Are there equivalents of the visual object token? How are object-identification conflicts between different perceptual systems resolved? Is the common assumption that “persistent object” is a fundamental innate category justified? How does the ability to identify and categorize objects relate to the ability to name and describe them using language? How are features that an individual object had in the past but does not have currently represented? How are categorical constraints on how objects move or act represented, and how do such constraints influence categorization and the re-identification of individuals? How do human beings re-identify objects, including each other, as persistent individuals across changes in location, context and features, even after gaps in observation lasting months or years? How do human capabilities for object categorization and re-identification over time relate to those of other species, and how do human infants develop these capabilities? What can modeling approaches such as cognitive robotics tell us about the answers to these questions? Primary research reports, reviews, and hypothesis and theory papers addressing questions relevant to the understanding of perceptual object segmentation, categorization and individual identification at any scale and from any experimental or modeling perspective are solicited for this Research Topic. Papers that review particular sets of issues from multiple disciplinary perspectives or that advance integrative hypotheses or models that take data from multiple experimental approaches into account are especially encouraged.

Download or read book Object Recognition Attention and Action written by Naoyuki Osaka and published by Springer. This book was released on 2007-09-18 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human object recognition is a classical topic both for philosophy and for the natural sciences. Ultimately, understanding of object recognition will be promoted by the cooperation of behavioral research, neurophysiology, and computation. This original book provides an excellent introduction to the issues that are involved. It contains chapters that address the ways in which humans and machines attend to, recognize, and act toward objects in the visual environment.

Download or read book Visual Object Tracking with Deep Neural Networks written by Pier Luigi Mazzeo and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.

Download or read book On the Difficulty of Feature Based Attentional Modulations in Visual Object Recognition A Modeling Study written by and published by . This book was released on 2004 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerous psychophysical experiments have shown an important role for attentional modulations in vision. Behaviorally, allocation of attention can improve performance in object detection and recognition tasks. At the neural level, attention increases firing rates of neurons in visual cortex whose preferred stimulus is currently attended to. However, it is not yet known how these two phenomena are linked, i.e., how the visual system could be tuned in a task-dependent fashion to improve task performance. To answer this question, we performed simulations with the HMAX model of object recognition in cortex [45]. We modulated firing rates of model neurons in accordance with experimental results about effects of featurebased attention on single neurons and measured changes in the model's performance in a variety of object recognition tasks. It turned out that recognition performance could only be improved under very limited circumstances and that attentional influences on the process of object recognition per se tend to display a lack of specificity or raise false alarm rates. These observations lead us to postulate a new role for the observed attention-related neural response modulations.

Download or read book The Perception of Multiple Objects written by Michael C. Mozer and published by MIT Press (MA). This book was released on 1991 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Perception of Multiple Objects describes a neurally inspired computational model of two-dimensional object recognition and spatial attention that can explain many characteristics of human visual perception. The model, called MORSEL (named for its ability to perform Multiple Object Recognition and attentional Selection), is unique in providing a broad and unified explanation for a wide range of experimental psychological data on visual perception and attention. Although it draws on existing theoretical perspectives from cognitive psychology, it is a fully mechanistic account, not just a functional-level theory. MORSEL has been trained to recognize letters and words in various positions on its "retina." Following training, it can also recognize several items at once, subject to capacity limitations. The model makes predictions about what sorts of information the visual system can process in parallel and what sorts must be processed serially. Through simulation experiments, chiefly in letter and word perception, MORSEL has been shown to account for a variety of psychological phenomena, including perceptual errors that arise when several items appear simultaneously in the visual field, facilitatory effects of context and redundant information, attentional phenomena, visual search performance, and behaviors exhibited by neurological patients with acquired dyslexia.

Download or read book Interactions of Visual Attention and Object Recognition written by Dirk Walther and published by . This book was released on 2006 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Selective Attention Neural Network for Object Recognition written by Xiaozhong Zhou and published by . This book was released on 1991 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Combining Corpus Co occurrence and Attention with Visual Features for Object Recognition written by James Mountstephens and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book View invariant Object Category Learning Recognition and Search How Spatial and Object Attention are Coordinated Using Surface based Attentional Shrouds written by Arash Fazl and published by . This book was released on 2007 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts that an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud." All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned, and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation.