activity
20192022
most citedFacial Action Unit Detection using 3D Facial Landmarks

3 citations · 8 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CV2022

Random Forest Regression for continuous affect using Facial Action Units

Saurabh Hinduja, Shaun Canavan, Liza Jivnani +2

In this paper we describe our approach to the arousal and valence track of the 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW). We extracted facial f…

cs.CV2021

Quantified Facial Expressiveness for Affective Behavior Analytics

Md Taufeeq Uddin, Shaun Canavan

The quantified measurement of facial expressiveness is crucial to analyze human affective behavior at scale. Unfortunately, methods for expressiveness quantification at the video f…

cs.HC2021

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing

Hamza Elhamdadi, Shaun Canavan, Paul Rosen

We present an approach utilizing Topological Data Analysis to study the structure of face poses used in affective computing, i.e., the process of recognizing human emotion. The app…

cs.CV20202 cited

Accounting for Affect in Pain Level Recognition

Md Taufeeq Uddin, Shaun Canavan, Ghada Zamzmi

In this work, we address the importance of affect in automated pain assessment and the implications in real-world settings. To achieve this, we curate a new physiological dataset b…

cs.CV2020

Quantified Facial Temporal-Expressiveness Dynamics for Affect Analysis

Md Taufeeq Uddin, Shaun Canavan

The quantification of visual affect data (e.g. face images) is essential to build and monitor automated affect modeling systems efficiently. Considering this, this work proposes qu…

cs.CV2020

Impact of Action Unit Occurrence Patterns on Detection

Saurabh Hinduja, Shaun Canavan, Saandeep Aathreya

Detecting action units is an important task in face analysis, especially in facial expression recognition. This is due, in part, to the idea that expressions can be decomposed into…