158 citations · 548 across the 24 of their papers we have counts for
38 papers
Generating near-infrared facial expression datasets with dimensional affect labels
Calvin Chen, Stefan Winkler
Facial expression analysis has long been an active research area of computer vision. Traditional methods mainly analyse images for prototypical discrete emotions; as a result, they…
Detecting Blurred Ground-based Sky/Cloud Images
Mayank Jain, Navya Jain, Yee Hui Lee +2
Ground-based whole sky imagers (WSIs) are being used by researchers in various fields to study the atmospheric events. These ground-based sky cameras capture visible-light images o…
Efficient Facial Expression Analysis For Dimensional Affect Recognition Using Geometric Features
Vassilios Vonikakis, Stefan Winkler
Despite their continued popularity, categorical approaches to affect recognition have limitations, especially in real-life situations. Dimensional models of affect offer important…
Morphset:Augmenting categorical emotion datasets with dimensional affect labels using face morphing
Vassilios Vonikakis, Dexter Neo, Stefan Winkler
Emotion recognition and understanding is a vital component in human-machine interaction. Dimensional models of affect such as those using valence and arousal have advantages over t…
Forecasting Precipitable Water Vapor Using LSTMs
Mayank Jain, Shilpa Manandhar, Yee Hui Lee +2
Long-Short-Term-Memory (LSTM) networks have been used extensively for time series forecasting in recent years due to their ability of learning patterns over different periods of ti…
Empirical Analysis of Overfitting and Mode Drop in GAN Training
Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler +2
We examine two key questions in GAN training, namely overfitting and mode drop, from an empirical perspective. We show that when stochasticity is removed from the training procedur…
Subjective Quality Assessment of Ground-based Camera Images
Lucie Lévêque, Soumyabrata Dev, Murhaf Hossari +2
Image quality assessment is critical to control and maintain the perceived quality of visual content. Both subjective and objective evaluations can be utilised, however, subjective…
Predicting Solar Irradiance in Singapore
T. A. Fathima, Vasudevan Nedumpozhimana, Yee Hui Lee +2
Solar irradiance is the primary input for all solar energy generation systems. The amount of available solar radiation over time under the local weather conditions helps to decide…
A Chaotic Approach on Solar Irradiance Forecasting
T. A. Fathima, Vasudevan Nedumpozhimana, Yee Hui Lee +2
We analyse the time series of solar irradiance measurements using chaos theory. The False Nearest Neighbour method (FNN), one of the most common methods of chaotic analysis is used…
Estimating Solar Irradiance Using Sky Imagers
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee +1
Ground-based whole sky cameras are extensively used for localized monitoring of clouds nowadays. They capture hemispherical images of the sky at regular intervals using a fisheye l…
A Data-Driven Approach for Accurate Rainfall Prediction
Shilpa Manandhar, Soumyabrata Dev, Yee Hui Lee +2
In recent years, there has been growing interest in using Precipitable Water Vapor (PWV) derived from Global Positioning System (GPS) signal delays to predict rainfall. However, th…
CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation
Soumyabrata Dev, Atul Nautiyal, Yee Hui Lee +1
We analyze clouds in the earth's atmosphere using ground-based sky cameras. An accurate segmentation of clouds in the captured sky/cloud image is difficult, owing to the fuzzy boun…
Recognition of Advertisement Emotions with Application to Computational Advertising
Abhinav Shukla, Shruti Shriya Gullapuram, Harish Katti +3
Advertisements (ads) often contain strong affective content to capture viewer attention and convey an effective message to the audience. However, most computational affect recognit…
Multi-label Cloud Segmentation Using a Deep Network
Soumyabrata Dev, Shilpa Manandhar, Yee Hui Lee +1
Different empirical models have been developed for cloud detection. There is a growing interest in using the ground-based sky/cloud images for this purpose. Several methods exist t…
Predicting GPS-based PWV Measurements Using Exponential Smoothing
Shilpa Manandhar, Soumyabrata Dev, Yee Hui Lee +1
Global Positioning System (GPS) derived precipitable water vapor (PWV) is extensively being used in atmospheric remote sensing for applications like rainfall prediction. Many appli…
Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions
Yasin Yazıcı, Bruno Lecouat, Chuan-Sheng Foo +4
We propose a GAN design which models multiple distributions effectively and discovers their commonalities and particularities. Each data distribution is modeled with a mixture of $…
PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their Relationship
Le Zhang, Songyou Peng, Stefan Winkler
Apparent personality and emotion analysis are both central to affective computing. Existing works solve them individually. In this paper we investigate if such high-level affect tr…
Investigating the generalizability of EEG-based Cognitive Load Estimation Across Visualizations
Viral Parekh, Maneesh Bilalpur, Sharavan Kumar +3
We examine if EEG-based cognitive load (CL) estimation is generalizable across the character, spatial pattern, bar graph and pie chart-based visualizations for the nback~task. CL i…
EEG-based Evaluation of Cognitive Workload Induced by Acoustic Parameters for Data Sonification
Maneesh Bilalpur, Mohan Kankanhalli, Stefan Winkler +1
Data Visualization has been receiving growing attention recently, with ubiquitous smart devices designed to render information in a variety of ways. However, while evaluations of v…
The Unusual Effectiveness of Averaging in GAN Training
Yasin Yazıcı, Chuan-Sheng Foo, Stefan Winkler +3
We examine two different techniques for parameter averaging in GAN training. Moving Average (MA) computes the time-average of parameters, whereas Exponential Moving Average (EMA) c…
Systematic Study of Weather Variables for Rainfall Detection
Shilpa Manandhar, Soumyabrata Dev, Yee Hui Lee +2
Numerous weather parameters affect the occurrence and amount of rainfall. Therefore, it is important to study these parameters and their interdependency. In this paper, different w…
A Data-driven Approach to Detecting Precipitation from Meteorological Sensor Data
Shilpa Manandhar, Soumyabrata Dev, Yee Hui Lee +2
Precipitation is dependent on a myriad of atmospheric conditions. In this paper, we study how certain atmospheric parameters impact the occurrence of rainfall. We propose a data-dr…
A Deep Network for Arousal-Valence Emotion Prediction with Acoustic-Visual Cues
Songyou Peng, Le Zhang, Yutong Ban +2
In this paper, we comprehensively describe the methodology of our submissions to the One-Minute Gradual-Emotion Behavior Challenge 2018.
High-Dynamic-Range Imaging for Cloud Segmentation
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee +1
Sky/cloud images obtained from ground-based sky-cameras are usually captured using a fish-eye lens with a wide field of view. However, the sky exhibits a large dynamic range in ter…