基于YOLOv7网络的人像目标检测

随着人工智能时代的到来,人类对工业智能化的需求变得愈加迫切。主要研究了YOLOv7网络和YOLOv7-tiny网络在人像识别领域的性能优劣,为今后在工业智能化领域人像识别的深入应用提供了一定支持。实验结果表明,对于人像目标的不同运动姿态、密度和所处环境,YOLOv7网络均可对人像目标进行准确识别和分割。由此可见,YOLOv7网络具有良好的检测能力和较强的鲁棒性,这也使其可以广泛应用于工厂车间、步行道路、汽车站等众多人员密集场所。

A matting method based on color distance and differential distance

A new matting algorithm based on color distance and differential distance is proposed to deal with the problem that many matting methods perform poorly with complex natural images.The proposed method combines local sampling with global sampling to select foreground and background pairs for unknown pixels and then a new cost function is constructed based on color distance and differential distance to further optimize the selected sample pairs.Finally,a quadratic objective function is used based on matte Laplacian coming from KNN matting which is added with texture feature.Through experiments on various test images,it is confirmed that the results obtained by the proposed method are more accurate than those obtained by traditional methods.The four-error-metrics comparison on benchmark dataset among several algorithms also proves the effectiveness of the proposed method.