Abstract
Life-logging devices are becoming ubiquitous, yet still processing and extracting information from the vast amount of data that is being captured is a very challenging task. We propose a method to find discriminative regions which we define as regions that are salient, consistent, repetitive and discriminative. We explain our fast and novel algorithm to discover the discriminative regions and show different applications for discriminative regions such as summarization, classification and image search. Our experiments show that our algorithm is able to find discriminative regions and discriminative patches in a short time and extracts great results on our life-logging SenseCam dataset.
Cite
CITATION STYLE
Moghimi, M., Kerr, J., Johnson, E., Godbole, S., & Belongie, S. (2015). Discriminative regions: A substrate for analyzing life-logging image sequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8936, pp. 357–368). Springer Verlag. https://doi.org/10.1007/978-3-319-14442-9_42
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