Controlling eye movements with hidden Markov models
作者： Raymond D. Rimey , Christopher M. Brown
DOI: 10.1007/BF00130489
关键词:
摘要: Advances in technology and active vision research allow encourage sequential visual information acquisition. Hidden Markov models (HMMs) can represent probabilistic sequences graph structures: here we explore their use controlling the acquisition of information. We include a brief tutorial with two examples: (1) input to derive an aspect (2) similarly finite state machine for control processing.
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