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Evaluation Result of the Interim Software

OMRON SENSING TECHNOLOGY RESEARCH CENTER. To: Hong Kong Baptist University. Evaluation Result of the Interim Software. Sep.2, 2002. Omron Corporation Sensing Technology Research Center Vision-based Human Understanding Technologies Laboratory. Thanks.

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Evaluation Result of the Interim Software

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  1. OMRON SENSING TECHNOLOGY RESEARCH CENTER To: Hong Kong Baptist University Evaluation Result of the Interim Software Sep.2, 2002 Omron Corporation Sensing Technology Research Center Vision-based Human Understanding Technologies Laboratory

  2. Thanks • Thanks to your considerable efforts, better results obtained with this interim software.

  3. How to Evaluate 3 1 2 4 5 6 OMRON employed the following evaluation criteria for the outline detection of the facial organ . Evaluation Criteria: ・ Distance between Ground truth and Detected position. (Normalized the width of face to 100 pixels) (See bellow figures: 4 points of open eye, 3 points of close eye and 6 points of mouth) Software version:・MD09Aug2002.zip Using Program: ・OMRON use one function (Fixed_DetectFeature) . ( To know the potential performance of the ASM Algorithm for mouth ) Eye(open) Mouth 1.In 2.Out 3.Upper 4.Lower 1.left 2.right 3.top of upper lip 4.bottom of upper lip 5. top of lower lip 6. bottom of lower lip 3 2 1 4 Eye(close) 1.In 2.Out 4.Lower 2 Ground Truth 1 4 Detected Position

  4. Evaluation Data Sets OMRON evaluated with following Data Sets. INC_EYEC INC_EYEO INC_MA INC_MI *1) The list of these errors : See appendix

  5. Summary of Evaluation • [Eye] • The number of error detections of right eye is more than the left eye. I guess that the different model or algorithm is used for the left and right eye detection. • The detection accuracy falls down due to lower eyelid, upper eyelid and eye blow. - I guess the main reason is the error of facial feature point detection. • [Mouth] • Top of upper lip and bottom of lower lip is more accurate.- The opened mouth, i.e. “A” and “I”, should be improved. The variety of the active shape models is important for robustness. • The detection accuracy falls down due to teeth and nose. • [ etc ] • Many face and feature point detection error occurred with high resolution images.

  6. Suggestion • Our goal is to construct the principle algorithm of the state estimation of facial organ until February 2003. It is important for us to develop the ASM algorithm for the outline detection of facial organ as soon as possible. • We need to investigate the cause of failure in detecting the outline of facial organ. We should consider the errors of ASM algorithm and the others separately. This is the reason why we should evaluate the outline detection • of facial organ using fixed corners of eyes and mouth. • In order to realize the last goal until February, OMRON want you to begin to concentrate the research of the state estimation of facial organ.

  7. Correct Examples Closed eye Wide opened Eye shape of ”A” Mouth shape of ”I” Mouth

  8. Error Example:Closed Eye INC_EYEC I guess the main reason is the error of facial feature detection Eye Brow Etc. Lower eyelid Too short -> The length of left and right eye feature points differ greatly.

  9. Error Examples:Wide opened Eye INC_EYEO Nonexistent relation of between outline of eye and outline of black eye Opened eye is mistaken as closed eye. Identify the inside eye and the black eye Influence of the lower eyelid Etc. Eye blow

  10. Error Examples:shape of ”A” Mouth INC_MA The left and right points of mouth are fixed landmark points. Can’t spread the model Upper-lower is wrong. This cases is too much. Influence of the teeth Don’t leach the Upper-upper. Influence of the Chin

  11. Error Examples: shape of ”I” Mouth INC_MI The left and right points of mouth are fixed landmark points. thin Upper-lip Influence of the nose. (Noise of nose) Influence of teeth? Can’t stretch the Upper-lower and Lower-Upper

  12. Error Examples: high resolution image (no.1) omron_a1fb1 These images were saved by JPG format. If I convert JPG to BMP, we got slightly different results. But Results is not so good.

  13. Error Example: high resolution image (no.2) omron_a1fb1 The accuracy of facial feature detection is low. Please check your software of face detection and facial feature detection.

  14. Appendix

  15. Detection Rate within 3pix (Left eye) Result

  16. Detection Rate within 3pix (Right eye) Result

  17. Detection Rate within 3pix (Mouth) Result

  18. Detection Rate within 5pix (Left eye) Result

  19. Detection Rate within 5pix (Right eye) Result

  20. Detection Rate within 5pix (Mouth) Result

  21. Detection Rate within 7pix (Left eye) Result

  22. Detection Rate within 7pix (Right eye) Result

  23. Detection Rate within 7pix Mouth) Result

  24. Speed(Only outline detection of facial organ Result

  25. The List of Error File

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