Automatic segmentation of mouse behavior using hidden Markov model
نویسندگان
چکیده
A common approach to analysis of mouse behavior recorder by video tracking systems employs manual segmentation and labeling of mouse activity into behavioral acts. Developed automatic methods allow segmentation only to lingering and progression segments, suffer from poor precision and require parameter tuning. We propose a novel approach based on hidden Markov model for simultaneous segmentation and labeling of mouse trajectory into behavior acts. The method uses manually labeled video sequences for training. The developed approach has shown promising results when applied for segmentation of mouse behavior in a novel environment.
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