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- W2624405149 abstract "In this paper, we investigate pedestrian detection from visible color imagery in a manner that reduces the number of false positives (FPs) per frame. We propose a simple way to eliminate many of such unwanted FPs that usually result from applying a state-of-the-art pedestrian object detector to a visible color image. The symmetric structure of pedestrian bodies can often be a good clue to distinguish them from non-pedestrians. Hence, each and every individual detected object (bounded box) in the initial step of detection is used to reconstruct some new symmetric-looking objects. If any of these objects are detected, they are confirmed to be a person; otherwise, they are omitted from the very first list of detected objects. Experimental results show how these FPs are removed using such a simple technique while maintaining the previous low miss rate." @default.
- W2624405149 created "2017-06-15" @default.
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- W2624405149 date "2017-03-29" @default.
- W2624405149 modified "2023-10-14" @default.
- W2624405149 title "Double Phase Pedestrian Detection with Minimal Number of False Positives per Image" @default.
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- W2624405149 doi "https://doi.org/10.1145/3070617.3070642" @default.
- W2624405149 hasPublicationYear "2017" @default.
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