User-adaptive models for recognizing food preparation activities

S. Stein, S.J. McKenna

    Research output: Chapter in Book/Report/Conference proceedingChapter

    7 Citations (Scopus)

    Abstract

    Recognizing complex activities is a challenging research problem, particularly in the presence of strong variability in the way activities are performed. Food preparation activities are prime examples, involving many different utensils and ingredients as well as high inter-person variability. Recognition models need to adapt to users in order to robustly account for differences between them. This paper presents three methods for user-adaptation: combining classifiers that were trained separately on generic and user-specific data, jointly training a single support vector machine from generic and user-specific data, and a weighted K-nearest-neighbor formulation with different probability mass assigned to generic and user-specific samples. The methods are evaluated on video and accelerometer data of people preparing mixed salads. A combination of generic and user-specific models considerably increased activity recognition accuracy and was shown to be particularly promising when data from only a limited number of training subjects was available.
    Original languageEnglish
    Title of host publicationCEA 2013 - Proceedings of the 5th International Workshop on Multimedia for Cooking and Eating Activities
    Pages39-44
    Number of pages6
    DOIs
    Publication statusPublished - 1 Jan 2013

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  • Student Theses

    Multi-Modal Recognition of Manipulation Activities through Visual Accelerometer Tracking, Relational Histograms, and User-Adaptation

    Author: Stein, S., 2014

    Supervisor: McKenna, S. (Supervisor)

    Student thesis: Doctoral ThesisDoctor of Philosophy

    File

    Datasets

    50 Salads

    McKenna, S. (Creator) & Stein, S. (Creator), University of Dundee, 2012

    Dataset

    File

    Cite this

    Stein, S., & McKenna, S. J. (2013). User-adaptive models for recognizing food preparation activities. In CEA 2013 - Proceedings of the 5th International Workshop on Multimedia for Cooking and Eating Activities (pp. 39-44) https://doi.org/10.1145/2506023.2506031