PROJECT TITLE :

Attention Driven Foveated Video Quality Assessment - 2014

ABSTRACT:

Distinction sensitivity of the human visual system to visual stimuli can be considerably laid low with several mechanisms, e.g., vision foveation and a focus. Existing studies on foveation based mostly video quality assessment solely take into consideration static foveation mechanism. This paper 1st proposes a sophisticated foveal imaging model to get the perceived representation of video by integrating visual attention into the foveation mechanism. For accurately simulating the dynamic foveation mechanism, a completely unique approach to predict video fixations is proposed by mimicking the essential functionality of eye movement. Consequently, an advanced distinction sensitivity function, derived from the attention driven foveation mechanism, is modeled and then integrated into a wavelet-based distortion visibility live to build a full reference attention driven foveated video quality (AFViQ) metric. AFViQ exploits adequately perceptual visual mechanisms in video quality assessment. Intensive evaluation results with respect to many publicly on the market eye-tracking and video quality databases demonstrate promising performance of the proposed video attention model, fixation prediction approach, and quality metric.


Did you like this research project?

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


PROJECT TITLE : Graph Attention Spatial-Temporal Network with Collaborative Global-Local Learning for Citywide Mobile Traffic Prediction ABSTRACT: It is becoming increasingly important for proactive network service provisioning
PROJECT TITLE : Representation Learning with Multi-level Attention for Activity Trajectory Similarity Computation ABSTRACT: The widespread adoption of GPS-enabled hardware and wireless communication technology has resulted in
PROJECT TITLE : Graph Neural Network for Fraud Detection via Spatial-temporal Attention ABSTRACT: Card fraud is a significant problem that results in significant financial losses for cardholders as well as the banks that issue
PROJECT TITLE : Multi-level Attention Network for Retinal Vessel Segmentation ABSTRACT: In the screening, diagnosis, treatment, and evaluation of a variety of cardiovascular and ophthalmologic diseases, automatic vessel segmentation
PROJECT TITLE : Interaction-Aware Spatio-Temporal Pyramid Attention Networks for Action Classification ABSTRACT: When it comes to CNN-based visual action recognition, the accuracy of the process could be improved by concentrating

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

Project Enquiry