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• W1977573448 abstract "Automatic person identification in TV series has gained popularity over the years. While most of the works rely on using face-based recognition, errors during tracking such as false positive face tracks are typically ignored. We propose a variety of methods to remove false positive face tracks and categorize the methods into confidence- and context-based. We evaluate our methods on a large TV series data set and show that up to 75% of the false positive face tracks are removed at the cost of 3.6% true positive tracks. We further show that the proposed method is general and applicable to other detectors or trackers." @default.
• W1977573448 created "2016-06-24" @default.
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• W1977573448 date "2014-10-01" @default.
• W1977573448 modified "2023-09-25" @default.
• W1977573448 title "Cleaning up after a face tracker: False positive removal" @default.
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• W1977573448 doi "https://doi.org/10.1109/icip.2014.7025050" @default.
• W1977573448 hasPublicationYear "2014" @default.
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