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Paper   IPM / Cognitive Sciences / 11511
School of Cognitive Sciences
  Title:   Attention control with reinforcement learning for face recognition under partial occlusion
1.  Ehsan Norouzi
2.  Majid Nili Ahmadabadi
3.  Babak Nadjar Arabi
  Status:   Published
  Journal: Machine Vision & Applications
  Vol.:  22
  Year:  2011
  Pages:   337-348
  Supported by:  IPM
In this paper a new method for handling occlusion in face recognition is presented. In this method the faces are partitioned into blocks and a sequential recognition structure is developed. Then, a spatial attention control strategy over the blocks is learned using reinforcement learning. The outcome of this learning is a sorted list of blocks according to their average importance in the face recognition task. In the recall mode, the sorted blocks are employed sequentially until a confident decision is made. Obtained results of various experiments on the AR face database demonstrate the superior performance of proposed method as compared with that of the holistic approach in the recognition of occluded faces.

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