Looking at People: Sensing for Ubiquitous and Wearable Computing

By Alex Pentland. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

453 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/f2b7a0c608ab2557b8897cddd1dd7ebd56978a85

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In Computer Vision and Pattern Recognition

In Electrical and Electronic Engineering

Citations in the corpus

Survey on Emotional Body Gesture Recognition (2018, background): “matic psychological research tools [141].”
Fuzzy human motion analysis: A review (2014, background): “[22] Alex Pentland Looking at people: sensing for ubiquitou s and wearable computing Reviewed the state-of-the-art of "looking at people" focus ing on person identification and surveillance monitoring.”
Facial Expression Analysis (2011, background): “Applications of facial expression analysis include marketing [105], perceptual user interfaces, human-robot interaction [124, 142, 98], drowsy driver detection [126], telenursing [29], pain assessment [79], analyzing mother-infant interaction [45], autism [83], social robotics [6, 18], facial animat”
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning (2005, background): “Detecting, tracking and identifying people, and interpreting human behavior are the capabilities required of pervasive computing and wearable devices in applications such as smart environments and perceptual user interfaces [31], [107].”
Data fusion for visual tracking with particles (2004, background): “…, including visual servoing (e.g., [34]), surveillance (e.g., [19]), gestural human–machine interfaces and smart environments (e.g., [11], [33], [38]), video compression (e.g., [56]), augmented reality and visual effects (e.g., [35]), motion capture (e.g., [36]), environmental imaging (e.g.,…”
Figure-ground segmentation improves handled object recognition in egocentric video (2010, background): “Early studies of wearable vision can be found in [14, 19].”
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition (2002, background): “Face recognition is largely motivated by the need for surveillance and security, telecommunication and digital libraries, human-computer intelligent interaction, and smart environments [33], [4], [8], [30].”
Recent developments in human motion analysis (2003, background): “Recently, a relevant study by Pentland [32] centered on person identiAcation, surveillance=monitoring, 3-Dmethods, and smart rooms=perceptual user interfaces to review the state of the art of “looking at people”.”
Detecting activities of daily living in first-person camera views (2012, background): “There has been a fair amount of work on everyday activity-recognition from the ubiquitous computing community [31, 39, 29] , much of it addressed from a “lifelogging” perspective [2, 30] .”
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose (2001, background): “Over the last few years, numerous algorithms have been proposed for face recognition, see surveys [59], [7], [17], [50].”
Compound facial expressions of emotion (2014, background): “Without an understanding of which AUs represent each category of emotion, it is impossible to understand naturalistic expressions and address fundamental problems in neuroscience (40), study psychiatric disorders (41), or design complex perceptual interfaces (42).”
Independent component analysis of Gabor features for face recognition (2003, background): “Facerecognitionresearchprovides thecuttingedgetechnologiesin commercial,law enforcement,andmilitary applications.”
Learning to recognize objects in egocentric activities (2011, background): “Early studies of wearable cameras can be found in [15, 18].”
Two-dimensional PCA: a new approach to appearance-based face representation and recognition (2004, background): “Since then, PCA has been widely investigated and has become one of the most successful approaches in face recognition [4], [5], [6], [7].”