2D facial landmark model design by combining key points and inserted points

Fangmei Chen, Yong Xu, Dapeng Zhang, Kai Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)


Abstract Facial landmarks can be used as a compact and effective representation of facial geometry. Although different facial landmark models (LMs) have been used for various face image analysis tasks, there are few works investigating the design of the LMs, which takes care of how many landmarks to use to represent facial geometry and where to locate them. Existing LMs are either not sufficient to approximate face shapes precisely or including many redundant landmarks. This paper aims to develop an optimized LM which can delicately represent facial geometry while keeping as few landmarks as possible. We divide the landmarks into two categories, namely key points (KPs) and inserted points (IPs). KPs include anatomical and mathematical landmarks which are defined with consideration of an anthropometry face model; IPs are pseudo-landmarks that help describe the face shape accurately. An iterative searching scheme is proposed to find a series of optimal positions for IPs until some acceptable error is obtained. The obtained LM includes 54 KPs and 44 IPs distributed on different facial regions. We compare our LM and other LMs with similar number of points in terms of shape approximation error and landmark detection error. Experimental results show the superiority of our LM in both criteria. The proposed LM is useful for applications that require delicate shape representations and promotes standardization of facial LMs.
Original languageEnglish
Article number10092
Pages (from-to)7858-7868
Number of pages11
JournalExpert Systems with Applications
Issue number21
Publication statusPublished - 2 Jul 2015


  • Approximation error
  • Geometric facial representation
  • Inserted point
  • Key point
  • Landmark model

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence


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