hand detection n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Hand Detection PowerPoint Presentation
Download Presentation
Hand Detection

Loading in 2 Seconds...

play fullscreen
1 / 10

Hand Detection - PowerPoint PPT Presentation


  • 198 Views
  • Uploaded on

Hand Detection. Zhong Zhang. Skin and motion detector. A skin color likelihood distribution and a non-skin color distribution, denoted as and respectively are proposed. The probability of a pixel, whose color vector is [ r,g,b ], being skin is defined using Bayes rule:

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Hand Detection' - reese-walter


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
hand detection

Hand Detection

Zhong Zhang

skin and motion detector
Skin and motion detector
  • A skin color likelihood distribution and a non-skin color distribution, denoted as and respectively are proposed.
  • The probability of a pixel, whose color vector is [r,g,b], being skin is defined using Bayes rule:
  • Motion detector is based on frame differencing which works as follows:
    • Let denote the intensity value at pixel , at the i-th frame.
    • By comparing with and , we compute a motion indicator value .
skin and motion detector1
Skin and Motion Detector

Top 1 candidate

Skin indicator

Motion indicator

Skin and motion indicator

result
Result

Mp: hand detection using multiple proposals. Sm: skin and motion detector. The detection is considered as correct if the distance between the center of the detection box and annotation box is less than half of face box width. The box size is [35 35].

result1
Result

Mp: hand detection using multiple proposals. Sm: skin and motion detector. The detection is considered as correct if the overlap score between detection and annotation is larger than 0.5

result5
Result

The detection is considered as correct if the overlap score between detection and annotation is larger than a threshold. In the this table, this threshold can be 0.3, 0.4 and 0.5