摘要
针对复杂道路场景的目标检测难以实现在移动设备上的实时目标检测问题,采用了MobileNet-SSD的目标检测框架,设计了一种用于视频的多目标检测组合网络框架LSTM-SSD。利用视频连续帧的信息时序关联,有效的提高检测的置信度,减少单一图像检测中存在的不稳定问题。通过与VGG-SSD\MobileNet-SSD两种检测网络模型的对比,实验表明,设计的检测网络模型在应对多目标、模糊、遮挡等干扰状况下,均能获得较好的检测效果。该模型的设计,可对无人驾驶实现实时目标检测提供依据和参考。
Aiming at the problem that it is difficult for mobile devices to realize real-time target detection of complex road scenes.based on MobileNet-SSD target detection framework,an LSTM-SSD combined model algorithm for multi-target detection of video is designed.The algorithm takes advantage of the temporal feature of the video to effectively improve the confidence of detection and reduce the instability problem in image detection.Compared with the two detection network models of VGG-SSD\MobileNet-SSD,the results show that the designed detection network model can obtain better detection results under multi-objective,fuzzy,occlusion and other interference conditions.The construction of the model can provide basis and reference for real-time target detection by driverless vehicles.
作者
李明明
雷菊阳
赵从健
LI Ming-ming;LEI Ju-yang;ZHAO Cong-jian(College of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《软件》
2019年第12期140-145,共6页
Software
