combining two human detection methods

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Mammo Image
Mammo Image 2016 年 2 月 14 日
コメント済み: LAKSHMI PRIYA B S 2017 年 5 月 3 日
Hi everyone,
I am trying to detect people in side a home, I tried HOG once and Viola-object detection upper body another time.
now I am thinking to combine between these two methods, could you please show me the ways for combining as I so junior in image processing.
thanks very much for any cooperation
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LAKSHMI PRIYA B S
LAKSHMI PRIYA B S 2017 年 5 月 3 日
Did you combine two methods?I am also doing project related to this.Can you please send me available code?My id is lakshmibalu621@gmail.com

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採用された回答

Dima Lisin
Dima Lisin 2016 年 2 月 15 日
To combine these two methods, you first have to run the image through both detectors. That will give you two sets of bounding boxes. You can check which bounding boxes overlap, and by how much using the bboxOverlapRatio function.
What you do next depends on what you are trying to achieve. If you want to reduce the false positives, then you can take only the cases where both methods detect the person, i.e. where there is an overlap between the bounding boxes from each detector. If you want to reduce false negatives, you can take the cases where either method detects a person. Or you can have some kind of weighting scheme depending on which method you trust more.
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Mammo Image
Mammo Image 2016 年 2 月 15 日
Thank you very much Dima really appreciate your response.
Thanks again

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その他の回答 (2 件)

Walter Roberson
Walter Roberson 2016 年 2 月 14 日
Give a "vote" to each of the detection methods -- not necessarily an equal vote. Any location detected as occupied by both algorithms would get full marks. Any location detected as occupied by only one of the algorithms would get partial marks. Make a decision based upon the scores at the location.
For example, suppose Viola is really good at finding a human face but not good at finding the outlines of the body, and suppose HOG is good for finding outlines but is not good at determining whether there is a face. Then when you applied both algorithms together you would find areas that the detection overlapped. You could then use those as "seeds" to grow the regions out to the largest surrounding area detected by either algorithm.
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Mammo Image
Mammo Image 2016 年 2 月 14 日
hi Roberson yes thanks, but actually I cant find the start in my way since I dont know how should I start with the combination process.
thanks

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Mammo Image
Mammo Image 2016 年 2 月 15 日
please I need the help to get the start of work .. any suggestion?

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