NullSpaceRDAR: Regularized discriminative adaptive nullspace for object tracking

作者：

Highlights：

• A novel joint-nullspace is carfully designed instead of feature space.

• An adaptive loss function is developed to train the bounding box estimation.

• Extensive experiments have been conducted to evaluate NullSpaceRDAR on six benchmarks.

摘要

•A novel joint-nullspace is carfully designed instead of feature space.•An adaptive loss function is developed to train the bounding box estimation.•Extensive experiments have been conducted to evaluate NullSpaceRDAR on six benchmarks.

论文关键词：Visual object tracking,Joint-nullspace,Convolutional neural network

论文评审过程：Received 28 June 2021, Revised 1 March 2022, Accepted 31 August 2022, Available online 14 September 2022, Version of Record 22 September 2022.

论文官网地址：https://doi.org/10.1016/j.imavis.2022.104550