Presenter(s)
Kevin Krucki, Binu Nair
Files
Download Project (1.7 MB)
Description
This research involves live human re-identification on multi-camera systems. Each frame of multiple cameras needs to be captured and analyzed with image processing methods. First, a histogram of oriented gradients (HOG) is performed to identify a person in each frame. Next, Local Binary Pattern (LBP) descriptors are used on each person to determine certain set features about then. Lastly, a red, green, blue (RGB) color histogram is performed on a specific body mask. Each body is then given a label based on their LBP and color histogram information and that label will be sent to a database. This label should be the same across all the cameras. The process should also happen live. The research will include analysis of the difference between using a static body mask and using pose estimation for a more accurate color histogram. Also, regional descriptors will be used to better describe the human body. Lastly, the difference between YCrCb and RGB color histograms will be shown.
Publication Date
4-9-2014
Project Designation
Graduate Research
Primary Advisor
Vijayan Asari
Primary Advisor's Department
Vision Lab
Keywords
Stander Symposium project
Disciplines
Arts and Humanities | Business | Education | Engineering | Life Sciences | Medicine and Health Sciences | Physical Sciences and Mathematics | Social and Behavioral Sciences
Recommended Citation
"Human Re-Identification in Multi-Camera Systems" (2014). Stander Symposium Projects. 464.
https://ecommons.udayton.edu/stander_posters/464
![Human Re-Identification in Multi-Camera Systems](https://ecommons.udayton.edu/stander_posters/1460/thumbnail.jpg)
Included in
Arts and Humanities Commons, Business Commons, Education Commons, Engineering Commons, Life Sciences Commons, Medicine and Health Sciences Commons, Physical Sciences and Mathematics Commons, Social and Behavioral Sciences Commons