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{
    "pk": 26103,
    "title": "A Deep Siamese Neural Network Learns the Human-Perceived SimilarityStructure of Facial Expressions Without Explicit Categories",
    "subtitle": null,
    "abstract": "In previous work, we showed that a simple neurocomputa-tional model The Model, or TM) trained on the Ekman &Friesen Pictures of Facial Affect (POFA) dataset to catego-rize the images into the six basic expressions can account forwide array of data (albeit from a single study) on facial ex-pression processing. The model demonstrated categorical per-ception of facial expressions, as well as the so-called facialexpression circumplex, a circular configuration based on MDSresults that places the categories in the order happy, surprise,fear, sadness, anger and disgust. Somewhat ironically, the cir-cumplex in TM was generated from the similarity between thecategorical outputs of the network, i.e., the six numbers rep-resenting the probability of the category given the face. Here,we extend this work by 1) using a new dataset, NimsStims,that is much larger than POFA, and is not as tightly controlledfor the correct Facial Action Units; 2) using a completely dif-ferent neural network architecture, a Siamese Neural Network(SNN) that maps two faces through twin networks into a 2Dsimilarity space; and 3) training the network only implicitly,based on a teaching signal that pairs of faces are in either inthe same or different categories. Our results show that in thissetting, the network learns a representation that is very similarto the original circumplex. Fear and surprise overlap, whichis consistent with the inherent confusability between these twofacial expressions. Our results suggest that humans evolvedin such a way that nearby emotions are represented by similarappearances.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "facial expressions; similarity structure; deepsiamese neural network; multidimensional scaling (MDS); fa-cial expression circumplex"
        }
    ],
    "section": "Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/6n45n1cf",
    "frozenauthors": [
        {
            "first_name": "Sanjeev",
            "middle_name": "Jagannatha",
            "last_name": "Rao",
            "name_suffix": "",
            "institution": "University of California San Diego",
            "department": ""
        },
        {
            "first_name": "Yufei",
            "middle_name": "",
            "last_name": "Wang",
            "name_suffix": "",
            "institution": "University of California San Diego",
            "department": ""
        },
        {
            "first_name": "Garrison",
            "middle_name": "W",
            "last_name": "Cottrell",
            "name_suffix": "",
            "institution": "University of California San Diego",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2016-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26103/galley/15739/download/"
        }
    ]
}