Literature DB >> 15875802

A video database of moving faces and people.

Alice J O'Toole1, Joshua Harms, Sarah L Snow, Dawn R Hurst, Matthew R Pappas, Janet H Ayyad, Hervé Abdi.   

Abstract

We describe a database of static images and video clips of human faces and people that is useful for testing algorithms for face and person recognition, head/eye tracking, and computer graphics modeling of natural human motions. For each person there are nine static "facial mug shots" and a series of video streams. The videos include a "moving facial mug shot," a facial speech clip, one or more dynamic facial expression clips, two gait videos, and a conversation video taken at a moderate distance from the camera. Complete data sets are available for 284 subjects and duplicate data sets, taken subsequent to the original set, are available for 229 subjects.

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Year:  2005        PMID: 15875802     DOI: 10.1109/TPAMI.2005.90

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  21 in total

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2.  Learning Faces as Concepts Improves Face Recognition by Engaging the Social Brain Network.

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4.  The Sabancı University Dynamic Face Database (SUDFace): Development and validation of an audiovisual stimulus set of recited and free speeches with neutral facial expressions.

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5.  Independent contributions of the face, body, and gait to the representation of the whole person.

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Journal:  Atten Percept Psychophys       Date:  2021-01       Impact factor: 2.199

6.  Compound facial expressions of emotion.

Authors:  Shichuan Du; Yong Tao; Aleix M Martinez
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7.  Social Trait Information in Deep Convolutional Neural Networks Trained for Face Identification.

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Journal:  Cogn Sci       Date:  2019-06

8.  Perceived similarity ratings predict generalization success after traditional category learning and a new paired-associate learning task.

Authors:  Stefania R Ashby; Caitlin R Bowman; Dagmar Zeithamova
Journal:  Psychon Bull Rev       Date:  2020-08

9.  Exploring techniques for vision based human activity recognition: methods, systems, and evaluation.

Authors:  Xin Xu; Jinshan Tang; Xiaolong Zhang; Xiaoming Liu; Hong Zhang; Yimin Qiu
Journal:  Sensors (Basel)       Date:  2013-01-25       Impact factor: 3.576

10.  A database of whole-body action videos for the study of action, emotion, and untrustworthiness.

Authors:  Bruce D Keefe; Matthias Villing; Chris Racey; Samantha L Strong; Joanna Wincenciak; Nick E Barraclough
Journal:  Behav Res Methods       Date:  2014-12
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