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Human behavior recognition based on fractal conditional random field

机译:基于分形条件随机场的人类行为识别

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摘要

In order to meet the demand of visual behavior recognition, we introduce Fractal Conditional Random Field (FCRF) model. FCRF model has improved Latent-Dynamic Conditional Random Field (LDCRF), and proposed the concept of fractal labels that define the integrity and directionality of human behavior. FCRF model overcomes real-time issues of the Hidden Conditional Random Field (HCRF) and the problem of label bias when the behavior transform. The experimental results show that the algorithm proposed in this paper has better recognition performance than Conditional Random Field (CRF), HCRF and LDCRF.
机译:为了满足视觉行为识别的需求,我们引入了分形条件随机场(FCRF)模型。 FCRF模型改进了潜在动态条件随机场(LDCRF),并提出了分形标签的概念,该分形标签定义了人类行为的完整性和方向性。 FCRF模型克服了行为转换时的隐藏条件随机场(HCRF)实时问题和标签偏差问题。实验结果表明,与条件随机场(CRF),HCRF和LDCRF相比,本文提出的算法具有更好的识别性能。

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