Using structured light for efficient depth edge detection

  • Authors:

  • Jiyoung Park;Cheolhwon Kim;Jaekeun Na;Juneho Yi;Matthew Turk

  • Affiliations:

  • Electronics and Telecommunications Research Institute (ETRI), Digital content Research Division, Republic of Korea;Nexteye Co., Ltd, Advanced Technology Institute, Republic of Korea;Sungkyunkwan University, School of Information and Communication Engineering, Republic of Korea;Sungkyunkwan University, School of Information and Communication Engineering, Republic of Korea;University of California, Santa Barbara, Computer Science Department, USA

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2008

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Abstract

This research describes a novel approach that accurately detects depth edges with cluttered inner texture edges effectively ignored. We strategically project structured light and exploit distortion of the light pattern in the structured light image along depth discontinuities to reliably detect depth edges. In practice, distortion along depth discontinuities may not occur or be large enough to detect depending on the distance from the camera or projector. We present methods that guarantee the occurrence of the distortion along depth discontinuities for a continuous range of object location. Experimental results show that the proposed method accurately detects depth edges of shapes of human hands and bodies as well as general objects.