From the Publisher: 
A Question of Identity 
Life on the Screen is a fascinating and wide-ranging investigation of the impact of computers and networking on society, peoples' perceptions of themselves, and the individual's relationship to machines. Sherry Turkle, a Professor of the Sociology of Science at MIT and a licensed psychologist, uses Internet MUDs (multi-user domains, or in older gaming parlance multi-user dungeons) as a launching pad for explorations of software design, user interfaces, simulation, artificial intelligence, artificial life, agents, "bots," virtual reality, and "the on-line way of life." 
Turkle's discussion of postmodernism is particularly enlightening. She shows how postmodern concepts in art, architecture, and ethics are related to concrete topics much closer to home, for example AI research (Minsky's "Society of Mind") and even MUDs (exemplified by students with X-window terminals who are doing homework in one window and simultaneously playing out several different roles in the same MUD in other windows). Those of you who have (like me) been turned off by the shallow, pretentious, meaningless paintings and sculptures that litter our museums of modern art may have a different perspective after hearing what Turkle has to say. 
This is a psychoanalytical book, not a technical one. However, software developers and engineers will find it highly accessible because of the depth of the author's technical understanding and credibility. Unlike most other authors in this genre, Turkle does not constantly jar the technically-literate reader with blatant errors or bogus assertions about how things work. Although I personally don't have time or patience for MUDs,view most of AI as snake-oil, and abhor postmodern architecture, I thought the time spent reading this book was an extremely good investment.

스크린 위의 삶 = Life on the screen : identity in the age of the internet

How have changes in media affected our everyday experience, behavior, and sense of identity? Such questions have generated endless arguments and speculations, but no thinker has addressed the issue with such force and originality as Joshua Meyrowitz in No Sense of Place. Advancing a daring and sophisticated theory, Meyrowitz shows how television and other electronic media have created new social situations that are no longer shaped by where we are or who is "with" us. While other media experts have limited the debate to message content, Meyrowitz focuses on the ways in which changes in media rearrange "who knows what about whom" and "who knows what compared to whom," making it impossible for us to behave with each other in traditional ways. No Sense of Place explains how the electronic landscape has encouraged the development of: -More adultlike children and more childlike adults; -More career-oriented women and more family-oriented men; and -Leaders who try to act more like the "person next door" and real neighbors who want to have a greater say in local, national, and international affairs. The dramatic changes fostered by electronic media, notes Meyrowitz, are neither entirely good nor entirely bad. In some ways, we are returning to older, pre-literate forms of social behavior, becoming "hunters and gatherers of an information age." In other ways, we are rushing forward into a new social world. New media have helped to liberate many people from restrictive, place-defined roles, but the resulting heightened expectations have also led to new social tensions and frustrations. Once taken-for-granted behaviors are now subject to constant debate and negotiation. The book richly explicates the quadruple pun in its title: Changes in media transform how we sense information and how we make sense of our physical and social places in the world.

No sense of place : the impact of electronic media on socialbehavior

Handbook of Autism and Pervasive Developmental Disorders

Multi-modal fusion network with multi-scale multi-path and cross-modal interactions for RGB-D salient object detection

https://jnnp.bmj.com/content/jnnp/60/5/596.1.full.pdf

Attentional Processing. The Brain's Art of Mindfulness

Research on visual attention in 360° content is crucial to understand how people perceive and interact with this immersive type of content and to develop efficient techniques for processing, encoding, delivering and rendering. And also to offer a high quality of experience to end users. The availability of public datasets is essential to support and facilitate research activities of the community. Recently, some studies have been presented analyzing exploration behaviors of people watching 360° videos, and a few datasets have been published. However, the majority of these works only consider head movements as proxy for gaze data, despite the importance of eye movements in the exploration of omnidirectional content. Thus, this paper presents a novel dataset of 360° videos with associated eye and head movement data, which is a follow-up to our previous dataset for still images [14]. Head and eye tracking data was obtained from 57 participants during a free-viewing experiment with 19 videos. In addition, guidelines on how to obtain saliency maps and scanpaths from raw data are provided. Also, some statistics related to exploration behaviors are presented, such as the impact of the longitudinal starting position when watching omnidirectional videos was investigated in this test. This dataset and its associated code are made publicly available to support research on visual attention for 360° content.

https://hal.archives-ouvertes.fr/hal-01994923/document

A dataset of head and eye movements for 360° videos

High dynamic range (HDR) signals fundamentally differ from the traditional low dynamic range (LDR) ones in that pixels are related (proportional) to the physical luminance in the scene (i.e. scene-referred). For that reason, the existing LDR video quality measurement methods may not be directly used for assessing quality in HDR videos. To address that, we present an objective HDR video quality measure (HDR-VQM) based on signal pre-processing, transformation, and subsequent frequency based decomposition. Video quality is then computed based on a spatio-temporal analysis that relates to human eye fixation behavior during video viewing. Consequently, the proposed method does not involve expensive computations related to explicit motion analysis in the HDR video signal, and is therefore computationally tractable. We also verified its prediction performance on a comprehensive, in-house subjective HDR video database with 90 sequences, and it was found to be better than some of the existing methods in terms of correlation with subjective scores (for both across sequence and per sequence cases). A software implementation of the proposed scheme is also made publicly available for free download and use. HighlightsThe paper presents one of the first objective method for high dynamic range video quality estimation.It is based on analysis of short term video segments taking into account human viewing behavior.The method described in the paper would be useful in scenarios where HDR video quality needs to be determined in an HDR video chain study.

Hdr-vqm

Observers' fixations exhibit a marked bias towards certain areas on the screen when viewing scenes on computer monitors. For instance, there exists a well-known "center-bias" which means that fixations are biased towards the center of the screen during the viewing of 2D still images. In the viewing of 3D content, stereoscopic displays enhance depth perception by the mean of binocular parallax. This additional depth cue has a great influence on guiding eye movements. Relatively little is known about the impact of binocular parallax on visual attention of the 3D content displayed on stereoscopic screen. Several studies mentioned that people tend to look preferably at the objects located at certain positions in depth. But studies proving or quantifying this depth-bias are still limited. In this paper, we conducted a binocular eye-tracking experiment by showing synthetic stimuli on a stereoscopic display. Observers were required to do a free-viewing task through passive polarized glasses. Gaze positions of both eyes were recorded and the depth of eyes' fixation was determined. The stimuli used in the experiment were designed in such a way that the center-bias and the depth-bias affect eye movements individually. Results indicate the existence of a depth-bias: objects closer to the viewer attract attention earlier than distant objects, and the number of fixations located on objects varies as a function of objects' depth. The closest object in a scene always attracts most fixations. The fixation distribution along depth also shows a convergent behavior as the viewing time increases.

/pdf/study-of-depth-bias-of-observers-in-free-viewing-of-still-16d4sysevz.pdf

Study of depth bias of observers in free viewing of still stereoscopic synthetic stimuli

In this paper, we investigate the visual attention modeling for stereoscopic video from the following two aspects. First, we build one large-scale eye tracking database as the benchmark of visual attention modeling for stereoscopic video. The database includes 47 video sequences and their corresponding eye fixation data. Second, we propose a novel computational model of visual attention for stereoscopic video based on Gestalt theory. In the proposed model, we extract the low-level features, including luminance, color, texture, and depth, from discrete cosine transform coefficients, which are used to calculate feature contrast for the spatial saliency computation. The temporal saliency is calculated by the motion contrast from the planar and depth motion features in the stereoscopic video sequences. The final saliency is estimated by fusing the spatial and temporal saliency with uncertainty weighting, which is estimated by the laws of proximity, continuity, and common fate in Gestalt theory. Experimental results show that the proposed method outperforms the state-of-the-art stereoscopic video saliency detection models on our built large-scale eye tracking database and one other database (DML-ITRACK-3D).

Visual Attention Modeling for Stereoscopic Video: A Benchmark and Computational Model

Virtual Reality (VR) provides the users with new immersive media experiences, offering the possibility to freely explore 360° content Understanding these new exploration behaviors is crucial for the development of efficient techniques for processing, coding, delivering and rendering omnidirectional content to offer the highest possible Quality of Experience (QoE) Progress has already been made on visual attention (VA) modeling for 360° content In this paper we briefly review the current status of research on this topic that led us to propose a benchmarking platform for evaluating and comparing the performance of models for saliency and scanpath prediction for 360° content This paper introduces the ‘UN Salient360! benchmark” platform featuring a dataset, a toolbox and a framework for evaluation of different class of models This online platform can be found in httns://salient360ls2nfr/

Matthieu Perreira Da Silva

Papers

A dataset of head and eye movements for 360° videos

Hdr-vqm

Study of depth bias of observers in free viewing of still stereoscopic synthetic stimuli

Visual Attention Modeling for Stereoscopic Video: A Benchmark and Computational Model

Introducing UN Salient360! Benchmark: A platform for evaluating visual attention models for 360° contents