3 citations · 9 across the 11 of their papers we have counts for
12 papers
Beyond the Fold: Quantifying Split-Level Noise and the Case for Leave-One-Dataset-Out AU Evaluation
Saurabh Hinduja, Gurmeet Kaur, Maneesh Bilalpur +2
Subject-exclusive cross-validation is the standard evaluation protocol for facial Action Unit (AU) detection, yet reported improvements are often small. We show that cross-validati…
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…
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…
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…
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…
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…
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…
Detecting Forged Facial Videos using convolutional neural network
Neilesh Sambhu, Shaun Canavan
In this paper, we propose to detect forged videos, of faces, in online videos. To facilitate this detection, we propose to use smaller (fewer parameters to learn) convolutional neu…
Facial Action Unit Detection using 3D Facial Landmarks
Saurabh Hinduja, Shaun Canavan
In this paper, we propose to detect facial action units (AU) using 3D facial landmarks. Specifically, we train a 2D convolutional neural network (CNN) on 3D facial landmarks, track…
Impact of multiple modalities on emotion recognition: investigation into 3d facial landmarks, action units, and physiological data
Diego Fabiano, Manikandan Jaishanker, Shaun Canavan
To fully understand the complexities of human emotion, the integration of multiple physical features from different modalities can be advantageous. Considering this, we present an…
Subject Identification Across Large Expression Variations Using 3D Facial Landmarks
Sk Rahatul Jannat, Diego Fabiano, Shaun Canavan +1
Landmark localization is an important first step towards geometric based vision research including subject identification. Considering this, we propose to use 3D facial landmarks f…
Studying the Impact of Mood on Identifying Smartphone Users
Khadija Zanna, Sayde King, Tempestt Neal +1
This paper explores the identification of smartphone users when certain samples collected while the subject felt happy, upset or stressed were absent or present. We employ data fro…