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Noise has been widely used to investigate the processing properties of various visual functions (e.g. detection, discrimination, attention, perceptual learning, averaging, crowding, face recognition), in various populations (e.g. older adults, amblyopes, migrainers, dyslexic children), using noise along various dimensions (e.g. pixel noise, orientation jitter, contrast jitter). The reason to use external noise is generally not to characterize visual processing in external noise per se, but rather to reveal how vision works in ordinary conditions when performance is limited by our intrinsic noise rather than externally added noise. For instance, reverse correlation aims at identifying the relevant information to perform a given task in noiseless conditions and measuring contrast thresholds in various noise levels can be used to understand the impact of intrinsic noise that limits sensitivity to noiseless stimuli. Why use noise? Since Fechner named it, psychophysics has always emphasized the systematic investigation of conditions that break vision. External noise raises threshold hugely and selectively. In hearing, Fletcher used noise in his famous critical-band experiments to reveal frequency-selective channels in hearing. Critical bands have been found in vision too. More generally, the big reliable effects of noise give important clues to how the system works. And simple models have been proposed to account for the effects of visual noise. As noise has been more widely used, questions have been raised about the simplifying assumptions that link the processing properties in noiseless conditions to measurements in external noise. For instance, it is usually assumed that the processing strategy (or mechanism) used to perform a task and its processing properties (e.g. filter tuning) are unaffected by the addition of external noise. Some have suggested that the processing properties could change with the addition of external noise (e.g. change in filter tuning or more lateral masking in noise), which would need to be considered before drawing conclusions about the processing properties in noiseless condition. Others have suggested that different processing properties (or mechanisms) could be solicited in low and high noise conditions, complicating the characterization of processing properties in noiseless condition based on processing properties identified in noise conditions. The current Research Topic probes further into what the effects of visual noise tell us about vision in ordinary conditions. Our Editorial gives an overview of the articles in this special issue.
Aimed at students taking a course on visual perception, this textbook considers what it means for a man, a monkey and a computer to perceive the world. After an introduction and a discussion of methods, the book deals with how the environment produces a physical effect, how the resulting "image" is processed by the brain or by computer algorithms in order to produce a perception of "something out there". It also discusses color, form, motion, distance, and also the sensing of three dimensionality, before dealing with visual perception and its role in awareness and consciousness. The book concludes with discussions of perceptual development, blindness, and visual disorders. Visual perception is by its very nature an interdisciplinary subject that requires a basic understanding of a range of topics from diverse fields, and this is a very readable guide to all students whether they come from a neuroscience, psychology, cognitive science, robotics, or philosophy background.
An interdisciplinary book that surveys experimental and theoretical discoveries concerning how a brain sees and how insights about biological vision can be used to develop more effective algorithms for image processing in technology.
The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part III includes the Advances in Image Manipulation Workshop and Challenges.
The six-volume set comprising LNCS volumes 6311 until 6313 constitutes the refereed proceedings of the 11th European Conference on Computer Vision, ECCV 2010, held in Heraklion, Crete, Greece, in September 2010. The 325 revised papers presented were carefully reviewed and selected from 1174 submissions. The papers are organized in topical sections on object and scene recognition; segmentation and grouping; face, gesture, biometrics; motion and tracking; statistical models and visual learning; matching, registration, alignment; computational imaging; multi-view geometry; image features; video and event characterization; shape representation and recognition; stereo; reflectance, illumination, color; medical image analysis.