most citedEstimating Visual Information From Audio Through Manifold Learning

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV20223 cited

Estimating Visual Information From Audio Through Manifold Learning

Fabrizio Pedersoli, Dryden Wiebe, Amin Banitalebi +3

We propose a new framework for extracting visual information about a scene only using audio signals. Audio-based methods can overcome some of the limitations of vision-based method…

eess.SP2018

A Technique Based on Chaos for Brain Computer Interfacing

A. Banitalebi, S. K. Setarehdan, G. A. Hossein-Zadeh

A user of Brain Computer Interface (BCI) system must be able to control external computer devices with brain activity. Although the proof-of-concept was given decades ago, the reli…

cs.MM2018

Robust LSB Watermarking Optimized for Local Structural Similarity

Amin Banitalebi, Said Nader-Esfahani, Alireza Nasiri Avanaki

Growth of the Internet and networked multimedia systems has emphasized the need for copyright protection of the media. Media can be images, audio clips, videos and etc. Digital wat…

eess.IV2018

Exploring the Distributed Video Coding in a Quality Assessment Context

A. Banitalebi, H. R. Tohidypour

In the popular video coding trend, the encoder has the task to exploit both spatial and temporal redundancies present in the video sequence, which is a complex procedure. As a resu…

eess.IV2018

A Perceptual Based Motion Compensation Technique for Video Coding

Amin Banitalebi, Said Nader-Esfahani, Alireza Nasiri Avanaki

Motion estimation is one of the important procedures in the all video encoders. Most of the complexity of the video coder depends on the complexity of the motion estimation step. T…