Search Results for author: Shaun Canavan

Found 11 papers, 0 papers with code

Random Forest Regression for continuous affect using Facial Action Units

no code implementations24 Mar 2022 Saurabh Hinduja, Shaun Canavan, Liza Jivnani, Sk Rahatul Jannat, V Sri Chakra Kumar

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).


Quantified Facial Expressiveness for Affective Behavior Analytics

no code implementations5 Oct 2021 Md Taufeeq Uddin, Shaun Canavan

The quantified measurement of facial expressiveness is crucial to analyze human affective behavior at scale.

Accounting for Affect in Pain Level Recognition

no code implementations15 Nov 2020 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.

Quantified Facial Temporal-Expressiveness Dynamics for Affect Analysis

no code implementations28 Oct 2020 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.

Impact of multiple modalities on emotion recognition: investigation into 3d facial landmarks, action units, and physiological data

no code implementations17 May 2020 Diego Fabiano, Manikandan Jaishanker, Shaun Canavan

Considering this, we present an analysis of 3D facial data, action units, and physiological data as it relates to their impact on emotion recognition.

Emotion Recognition

Detecting Forged Facial Videos using convolutional neural network

no code implementations17 May 2020 Neilesh Sambhu, Shaun Canavan

In this paper, we propose to detect forged videos, of faces, in online videos.

Subject Identification Across Large Expression Variations Using 3D Facial Landmarks

no code implementations17 May 2020 Sk Rahatul Jannat, Diego Fabiano, Shaun Canavan, Tempestt Neal

Landmark localization is an important first step towards geometric based vision research including subject identification.

Studying the Impact of Mood on Identifying Smartphone Users

no code implementations27 Jun 2019 Khadija Zanna, Sayde King, Tempestt Neal, Shaun Canavan

This paper explores the identification of smartphone users when certain samples collected while the subject felt happy, upset or stressed were absent or present.

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