...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of visual communication & image representation >Adaptive visual target detection and tracking using weakly supervised incremental appearance learning and RGM-PHD tracker
【24h】

Adaptive visual target detection and tracking using weakly supervised incremental appearance learning and RGM-PHD tracker

机译：使用弱监督的增量外观学习和RGM-PHD跟踪器进行自适应视觉目标检测和跟踪

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Multiple visual target tracking is a challenging problem due to various uncertainties including occlusion, miss-detection and noisy measurement. Most tracking approaches utilize an object-specific detector, pre-trained on many labeled images, to provide suitable measurements for their tracking system. In this paper, we use a simple background subtraction detector which only needs the background image to localize targets independent of their shape or type. In order to cope with the uncertainties resulted by the detector, we propose an adaptive appearance model and develop an incremental appearance learning algorithm to learn the target appearances in time. The proposed method employs the background information and our defined keypoints' miss-matched history to adapt the target appearances within different frames. Furthermore, we combine Refined Gaussian Mixture Probability Hypothesis Density (RGM-PHD) tracker with the detectors to keep target trajectories and handle uncertainties. The experiments conducted on several video datasets show the effectiveness of our proposed method. (C) 2015 Elsevier Inc. All rights reserved.
机译：由于各种不确定性，包括遮挡，误检和噪声测量，多视觉目标跟踪是一个具有挑战性的问题。大多数跟踪方法利用在许多标记图像上进行预训练的特定对象检测器，以为其跟踪系统提供合适的测量值。在本文中，我们使用一个简单的背景减法检测器，该检测器仅需要背景图像即可对目标进行定位，而与目标的形状或类型无关。为了应对检测器带来的不确定性，我们提出了一种自适应外观模型，并开发了一种增量式外观学习算法来及时学习目标外观。所提出的方法利用背景信息和我们定义的关键点的失配历史来适应不同帧内的目标外观。此外，我们将精细的高斯混合概率假设密度（RGM-PHD）跟踪器与检测器相结合，以保持目标轨迹并处理不确定性。在几个视频数据集上进行的实验证明了我们提出的方法的有效性。 （C）2015 Elsevier Inc.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号