iCanDraw: using sketch recognition and corrective feedback to assist a user in drawing human faces

  • Authors:

  • Daniel Dixon;Manoj Prasad;Tracy Hammond

  • Affiliations:

  • Texas A&M University, College Station, TX, USA;Texas A&M University, College Station, TX, USA;Texas A&M University, College Station, TX, USA

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2010

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Abstract

When asked to draw, many people are hesitant because they consider themselves unable to draw well. This paper describes the first system for a computer to provide direction and feedback for assisting a user to draw a human face as accurately as possible from an image. Face recognition is first used to model the features of a human face in an image, which the user wishes to replicate. Novel sketch recognition algorithms were developed to use the information provided by the face recognition to evaluate the hand-drawn face. Two design iterations and user studies led to nine design principles for providing such instruction, presenting reference media, giving corrective feedback, and receiving actions from the user. The result is a proof-of-concept application that can guide a person through step-by-step instruction and generated feedback toward producing his/her own sketch of a human face in a reference image.