基于匹配层融合的识别算法研究与实现

Research and implementation of recognition algorithm based on matching layer fusion

提出一种基于音视频匹配层自适应加权融合的身份识别方法。在不同程度的噪声情况下,图像与声音的识别率会随噪声的增强而降低,凭借单个生物模态的识别,难以达到很好的预测结果;而且两种模态融合时的权值不同,融合系统的稳定性效果也不同。采用双模态的自适应加权融合不仅可以有效地弥补不同生物模态识别之间的优缺点,而且可以自适应选择最优的权值进行决策。实验表明,该方法的理论推测成立,比单模态的身份识别具有更高的识别率与鲁棒性。

This paper proposes an adaptive weighted fusion based on audio-video matching layer.In the case of different degree of noise,the recognition degree of image and sound will decrease with the increase of noise.And the weight of the two modes is different,the stability effect of the fusion system is also different.The adaptive weighted fusion of two modes can not only make up the advantages and disadvantages of different biological modes,but also choose the optimal weight to make the decision.Experiments show that the proposed method is feasible and has higher recognition rate and robustness than single mode identification.