Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach

09/10/2017
by   Bowen Cheng, et al.
1

Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications. However, the inadequate network bandwidth often limits the spatial resolution of the transmitted video, which will heavily degrade the recognition reliability. We develop a novel framework to achieve robust emotion recognition from low bit rate video. While video frames are downsampled at the encoder side, the decoder is embedded with a deep network model for joint super-resolution (SR) and recognition. Notably, we propose a novel max-mix training strategy, leading to a single "One-for-All" model that is remarkably robust to a vast range of downsampling factors. That makes our framework well adapted for the varied bandwidths in real transmission scenarios, without hampering scalability or efficiency. The proposed framework is evaluated on the AVEC 2016 benchmark, and demonstrates significantly improved stand-alone recognition performance, as well as rate-distortion (R-D) performance, than either directly recognizing from LR frames, or separating SR and recognition.

READ FULL TEXT
research
06/14/2023

SAFER: Situation Aware Facial Emotion Recognition

In this paper, we present SAFER, a novel system for emotion recognition ...
research
05/30/2018

Context-aware Cascade Attention-based RNN for Video Emotion Recognition

Emotion recognition can provide crucial information about the user in ma...
research
04/23/2019

A Personalized Affective Memory Neural Model for Improving Emotion Recognition

Recent models of emotion recognition strongly rely on supervised deep le...
research
01/26/2021

Developing emotion recognition for video conference software to support people with autism

We develop an emotion recognition software for the use with a video conf...
research
08/16/2014

Real-time emotion recognition for gaming using deep convolutional network features

The goal of the present study is to explore the application of deep conv...
research
08/02/2020

Deep Multi-modality Soft-decoding of Very Low Bit-rate Face Videos

We propose a novel deep multi-modality neural network for restoring very...

Please sign up or login with your details

Forgot password? Click here to reset