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Jeffrey F. Cohn

5 accepted papers

2016

Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis

CVPR 2016poster

Emotion is expressed in multiple modalities, yet most research has considered at most one or two. This stems in part from the lack of large, diverse, well-annotated, multimodal databases with which to develop and test algorithms. We present a well-annotated, multimodal, multidimensional spontaneous…

Cited by 521PDFScholar
2016

Self-Adaptive Matrix Completion for Heart Rate Estimation From Face Videos Under Realistic Conditions

CVPR 2016oral

Recent studies in computer vision have shown that, while practically invisible to a human observer, skin color changes due to blood flow can be captured on face videos and, surprisingly, be used to estimate the heart rate (HR). While considerable progress has been made in the last few years, still m…

Cited by 413PDFScholar
2015

Confidence Preserving Machine for Facial Action Unit Detection

ICCV 2015poster

Varied sources of error contribute to the challenge of facial action unit detection. Previous approaches address specific and known sources. However, many sources are unknown. To address the ubiquity of error, we propose a Confident Preserving Machine (CPM) that follows an easy-to-hard classificatio…

Cited by 82PDFScholar
2015

Joint Patch and Multi-Label Learning for Facial Action Unit Detection

CVPR 2015poster

The face is one of the most powerful channel of non-verbal communication. The most commonly used taxonomy to describe facial behaviour is the Facial Action Coding System (FACS). FACS segments the visible effects of facial muscle activation into 30+ action units (AUs). AUs, which may occur alone an…

Cited by 246SourcePDFScholar
2015

Unsupervised Synchrony Discovery in Human Interaction

ICCV 2015poster

People are inherently social. Social interaction plays an important and natural role in human behavior. Most computational methods focus on individuals alone rather than in social context. They also require labelled training data. We present an unsupervised approach to discover interpersonal synchro…

Cited by 19PDFScholar