A method of extracting target trajectory by deep convolution network in infrared images

Tianwei Yang; Jungang Yang; Yang Sun; Wei An; Jing Wu

doi:10.1117/12.2557617

3 January 2020 A method of extracting target trajectory by deep convolution network in infrared images

Tianwei Yang, Jungang Yang, Yang Sun, Wei An, Jing Wu

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 1137310 (2020) https://doi.org/10.1117/12.2557617
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

The fully convolution network is a very powerful visual model that can be used to extract features in an image. We improved a network model that can be used for end-to-end, pixel-to-pixel training to extract target motion trajectories in infrared images. The dataset used in our training comes from the simulation dataset produced by the public infrared dataset combined with the simulation trajectory. In order to enhance the model’s robustness, we add the pepper and salt noise and white noise to the simulated image, and use image augmentation to increase the number of the image. We achieved highly train and test accuracy in our simulation dataset.

Citation Download Citation

Tianwei Yang, Jungang Yang, Yang Sun, Wei An, and Jing Wu "A method of extracting target trajectory by deep convolution network in infrared images", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137310 (3 January 2020); https://doi.org/10.1117/12.2557617

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