PROJECT TITLE :

Perceptual Experience Analysis for Tone-mapped HDR Videos Based on EEG and Peripheral Physiological Signals

ABSTRACT:

High dynamic range (HDR) imaging has been attracting abundant attention as a technology that may provide immersive expertise. Its ultimate goal is to produce better quality of expertise (QoE) via enhanced distinction. In this paper, we tend to analyze perceptual experience of tone-mapped HDR videos both explicitly by conducting a subjective questionnaire assessment and implicitly by using EEG and peripheral physiological signals. From the results of the subjective assessment, it is revealed that tone-mapped HDR videos are a lot of interesting and a lot of natural, and provide better quality than low dynamic range (LDR) videos. Physiological signals were recorded throughout watching tone-mapped HDR and LDR videos, and classification systems are made to explore perceptual difference captured by the physiological signals. Important distinction in the physiological signals is observed between tone-mapped HDR and LDR videos in the classification underneath each a subject matter-dependent and a theme-freelance scenarios. Additionally, vital distinction in the signals between high versus low perceived distinction and overall quality is detected via classification below the topic-dependent state of affairs. Moreover, it's shown that options extracted from the gamma frequency band are effective for classification.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Attention in Reasoning Dataset, Analysis, and Modeling ABSTRACT: Although attention has become an increasingly popular component in deep neural networks for the purpose of both interpreting data and improving
PROJECT TITLE : Efficient Evaluation of Image Quality via Deep-Learning Approximation of Perceptual Metrics ABSTRACT: An important role in the evaluation of complicated image processing algorithms is played by image metrics based
PROJECT TITLE : A Perceptual Distinguishability Predictor For JND-Noise-Contaminated Images ABSTRACT: These models are commonly used to estimate perceptual redundancy in images and videos. You can use a typical JND model evaluation
PROJECT TITLE :Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018ABSTRACT:Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate
PROJECT TITLE :Design, Analysis, and Implementation of ARPKI: An Attack-Resilient Public-Key Infrastructure - 2018ABSTRACT:This Transport Layer Security (TLS) Public-Key Infrastructure (PKI) is based on a weakest-link security

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry