Moving object detection and tracking Using Convolutional Neural Networks

被引:0
|
作者
Mane, Shraddha [1 ]
Mangale, Supriya [1 ]
机构
[1] MKSSSs Cummins Coll Engn Women, Dept Elect & Telecommun, Pune, Maharashtra, India
关键词
CNN; Object detection; TensorFlow; Tracking;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The object detection and tracking is the important steps of computer vision algorithm. The robust object detection is the challenge due to variations in the scenes. Another biggest challenge is to track the object in the occlusion conditions. Hence in this approach, the moving objects detection using TensorFlow object detection API. Further the location of the detected object is pass to the object tracking algorithm. A novel CNN based object tracking algorithm is used for robust object detection. The proposed approach is able to detect the object in different illumination and occlusion. The proposed approach achieved the accuracy of 90.88% on self generated image sequences.
引用
收藏
页码:1809 / 1813
页数:5
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