Cascade of Boolean detector combinations

Katariina Mahkonen, Tuomas Virtanen, Joni Kämäräinen

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    This paper considers a scenario when we have multiple pre-trained detectors for detecting an event and a small dataset for training a combined detection system. We build the combined detector as a Boolean function of thresholded detector scores and implement it as a binary classification cascade. The cascade structure is computationally efficient by providing the possibility to early termination. For the proposed Boolean combination function, the computational load of classification is reduced whenever the function becomes determinate before all the component detectors have been utilized. We also propose an algorithm, which selects all the needed thresholds for the component detectors within the proposed Boolean combination. We present results on two audio-visual datasets, which prove the efficiency of the proposed combination framework. We achieve state-of-the-art accuracy with substantially reduced computation time in laughter detection task, and our algorithm finds better thresholds for the component detectors within the Boolean combination than the other algorithms found in the literature.

    Original languageEnglish
    Article number61
    JournalEurasip Journal on Image and Video Processing
    Publication statusPublished - Dec 2018
    Publication typeA1 Journal article-refereed


    • Binary classification
    • Boolean combination
    • Classification cascade

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Signal Processing
    • Information Systems
    • Electrical and Electronic Engineering


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