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Rank Pooling for Action Recognition

Fernando, Basura; Gavves, Efstratios; Oramas Mogrovejo, Jose Antonio; Ghodrati, Amir; Tuytelaars, Tinne

Description

We propose a function-based temporal pooling method that captures the latent structure of the video sequence data - e.g., how frame-level features evolve over time in a video. We show how the parameters of a function that has been fit to the video data can serve as a robust new video representation. As a specific example, we learn a pooling function via ranking machines. By learning to rank the frame-level features of a video in chronological order, we obtain a new representation that captures...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Journal article
URI: http://hdl.handle.net/1885/247695
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI: 10.1109/TPAMI.2016.2558148

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