scholarly journals CNN-Based Multi-Modal Camera Model Identification on Video Sequences

2021 ◽  
Vol 7 (8) ◽  
pp. 135
Author(s):  
Davide Dal Cortivo ◽  
Sara Mandelli ◽  
Paolo Bestagini ◽  
Stefano Tubaro
Keyword(s):  
Visual Information ◽  
Model Identification ◽  
Video Sequences ◽  
Future Research ◽  
Camera Model ◽  
Identification Task ◽  
Multimedia Forensics ◽  
Identification Methods ◽  
Social Media Platforms ◽  
Audio Information

Identifying the source camera of images and videos has gained significant importance in multimedia forensics. It allows tracing back data to their creator, thus enabling to solve copyright infringement cases and expose the authors of hideous crimes. In this paper, we focus on the problem of camera model identification for video sequences, that is, given a video under analysis, detecting the camera model used for its acquisition. To this purpose, we develop two different CNN-based camera model identification methods, working in a novel multi-modal scenario. Differently from mono-modal methods, which use only the visual or audio information from the investigated video to tackle the identification task, the proposed multi-modal methods jointly exploit audio and visual information. We test our proposed methodologies on the well-known Vision dataset, which collects almost 2000 video sequences belonging to different devices. Experiments are performed, considering native videos directly acquired by their acquisition devices and videos uploaded on social media platforms, such as YouTube and WhatsApp. The achieved results show that the proposed multi-modal approaches significantly outperform their mono-modal counterparts, representing a valuable strategy for the tackled problem and opening future research to even more challenging scenarios.

scholarly journals Media forensics on social media platforms: a survey

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Cecilia Pasquini ◽  
Irene Amerini ◽  
Giulia Boato
Keyword(s):  
Social Media ◽  
Digital Media ◽  
Visual Information ◽  
Open Systems ◽  
Forensic Analysis ◽  
Provenance Analysis ◽  
Multimedia Forensics ◽  
Media Forensics ◽  
Media Objects ◽  
Social Media Platforms

AbstractThe dependability of visual information on the web and the authenticity of digital media appearing virally in social media platforms has been raising unprecedented concerns. As a result, in the last years the multimedia forensics research community pursued the ambition to scale the forensic analysis to real-world web-based open systems. This survey aims at describing the work done so far on the analysis of shared data, covering three main aspects: forensics techniques performing source identification and integrity verification on media uploaded on social networks, platform provenance analysis allowing to identify sharing platforms, and multimedia verification algorithms assessing the credibility of media objects in relation to its associated textual information. The achieved results are highlighted together with current open issues and research challenges to be addressed in order to advance the field in the next future.

Situational Factors Competing for Attention

2010 ◽  
Vol 22 (1) ◽  
pp. 2-13 ◽  
Author(s):  
Weiyu Zhang ◽  
Se-Hoon Jeong ◽  
Martin Fishbein†
Keyword(s):  
Task Performance ◽  
Visual Information ◽  
Situational Factors ◽  
Sexual Content ◽  
Sexually Explicit ◽  
Explicit Content ◽  
Audio Information

This study investigates how multitasking interacts with levels of sexually explicit content to influence an individual’s ability to recognize TV content. A 2 (multitasking vs. nonmultitasking) by 3 (low, medium, and high sexual content) between-subjects experiment was conducted. The analyses revealed that multitasking not only impaired task performance, but also decreased TV recognition. An inverted-U relationship between degree of sexually explicit content and recognition of TV content was found, but only when subjects were multitasking. In addition, multitasking interfered with subjects’ ability to recognize audio information more than their ability to recognize visual information.

A Survey of Computational Methods for Online Mental State Assessment on Social Media

2021 ◽  
Vol 2 (2) ◽  
pp. 1-31
Author(s):  
Esteban A. Ríssola ◽  
David E. Losada ◽  
Fabio Crestani
Keyword(s):  
Social Media ◽  
Mental Disorders ◽  
Mental State ◽  
Extraction Process ◽  
State Assessment ◽  
Future Research ◽  
Linguistic Markers ◽  
Online Social Media ◽  
Suicide Behaviour ◽  
Social Media Platforms

Mental state assessment by analysing user-generated content is a field that has recently attracted considerable attention. Today, many people are increasingly utilising online social media platforms to share their feelings and moods. This provides a unique opportunity for researchers and health practitioners to proactively identify linguistic markers or patterns that correlate with mental disorders such as depression, schizophrenia or suicide behaviour. This survey describes and reviews the approaches that have been proposed for mental state assessment and identification of disorders using online digital records. The presented studies are organised according to the assessment technology and the feature extraction process conducted. We also present a series of studies which explore different aspects of the language and behaviour of individuals suffering from mental disorders, and discuss various aspects related to the development of experimental frameworks. Furthermore, ethical considerations regarding the treatment of individuals’ data are outlined. The main contributions of this survey are a comprehensive analysis of the proposed approaches for online mental state assessment on social media, a structured categorisation of the methods according to their design principles, lessons learnt over the years and a discussion on possible avenues for future research.

Reliable Camera Model Identification Using Sparse Gaussian Processes

2021 ◽  
pp. 1-1
Author(s):  
Benedikt Lorch ◽  
Franziska Schirrmacher ◽  
Anatol Maier ◽  
Christian Riess
Keyword(s):  
Gaussian Processes ◽  
Model Identification ◽  
Camera Model

A study of co-occurrence based local features for camera model identification

2016 ◽  
Vol 76 (4) ◽  
pp. 4765-4781 ◽  
Author(s):  
Francesco Marra ◽  
Giovanni Poggi ◽  
Carlo Sansone ◽  
Luisa Verdoliva
Keyword(s):  
Model Identification ◽  
Local Features ◽  
Camera Model

Understanding the Experiences of Anger in the Onset and Progression of Psoriasis: A Qualitative Study Using Social Media (Preprint)

2021 ◽  
Author(s):  
Olivia Hughes ◽  
Rachael Hunter
Keyword(s):  
Social Media ◽  
Qualitative Interviews ◽  
Psychosocial Interventions ◽  
Skin Condition ◽  
Future Research ◽  
Social Media Platforms ◽  
Chronic Skin ◽  
Skin Conditions ◽  
The Impact

BACKGROUND Psoriasis is a chronic inflammatory skin condition, which can be affected by stress. Living with psoriasis can trigger negative emotions, which may influence quality of life. OBJECTIVE This study explored the experiences of people with psoriasis with attention to the potential role of anger in the onset and progression of the chronic skin condition. METHODS Semi-structured qualitative interviews were conducted with twelve participants (n=5 females, n=7 males) recruited online from an advert on a patient charity’s social media platforms. Data were transcribed and analysed using thematic analysis. RESULTS Four key themes were identified: (1) ‘I get really angry with the whole situation:’ anger at the self and others, (2) the impact of anger on psoriasis: angry skin, (3) shared experiences of distress, and (4) moving past anger to affirmation. CONCLUSIONS Findings suggest that anger can have a perceived impact on psoriasis through contributing to sensory symptoms and unhelpful coping cycles and point to a need for enhanced treatment with more psychological support. The findings also highlight the continued stigma which exists for people living with skin conditions and how this may contribute to, and sustain, anger for those individuals. Future research could usefully focus on developing targeted psychosocial interventions to promote healthy emotional coping with psoriasis.

scholarly journals Retention Of Cardiac Auscultation Skill Requires Paired Visual And Audio Information In New Learners

2008 ◽  
Vol 2 (2) ◽  
Author(s):  
Glenn Nordehn ◽  
Spencer Strunic ◽  
Tom Soldner ◽  
Nicholas Karlisch ◽  
Ian Kramer ◽  
...  
Keyword(s):  
Visual Information ◽  
Heart Sound ◽  
Heart Sounds ◽  
Sound Recognition ◽  
Cardiac Auscultation ◽  
Time Period ◽  
Significant Difference ◽  
Post Test ◽  
Short Time ◽  
Audio Information

Introduction: Cardiac auscultation accuracy is poor: 20% to 40%. Audio-only of 500 heart sounds cycles over a short time period significantly improved auscultation scores. Hypothesis: adding visual information to an audio-only format, significantly (p<.05) improves short and long term accuracy. Methods: Pre-test: Twenty-two 1st and 2nd year medical student participants took an audio-only pre-test. Seven students comprising our audio-only training cohort heard audio-only, of 500 heart sound repetitions. 15 students comprising our paired visual with audio cohort heard and simultaneously watched video spectrograms of the heart sounds. Immediately after trainings, both cohorts took audio-only post-tests; the visual with audio cohort also took a visual with audio post-test, a test providing audio with simultaneous video spectrograms. All tests were repeated in six months. Results: All tests given immediately after trainings showed significant improvement with no significant difference between the cohorts. Six months later neither cohorts maintained significant improvement on audio-only post-tests. Six months later the visual with audio cohort maintained significant improvement (p<.05) on the visual with audio post-test. Conclusions: Audio retention of heart sound recognition is not maintained if: trained using audio-only; or, trained using visual with audio. Providing visual with audio in training and testing allows retention of auscultation accuracy. Devices providing visual information during auscultation could prove beneficial.

scholarly journals Impacting the B2B-Business Development Process: Social Media Usage within a Global Software Environment

2020 ◽  
Vol 5 (1) ◽  
pp. 1-11
Author(s):  
Werner Krings
Keyword(s):  
Social Media ◽  
Development Process ◽  
Two Dimensions ◽  
Business Development ◽  
Future Research ◽  
Software Environment ◽  
Media Usage ◽  
Process Sequence ◽  
New Business ◽  
Social Media Platforms

The thesis aims to explore and explain how Social Media impacts the B2B-Business Development process in a global software environment. Mixed-methods uncover the leading media platforms applied in the Business Development process cycle. The thesis produced a model, illustrating two dimensions of Social Media Business Usage, four critical Business Development process phases, and their impact on Performance mediated by Social Capital. To extend generalizability, future research may focus on testing the model for New Business Development exclusively. Significant contributions are classifying relevant Social Media platforms, distilling the process phases with the greatest impact on performance. The creation of new indices advances the performance discussion, and the typology of Business Developers capitalises on optimising the process sequence.

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