Effective 3D object detection based on detector and tracker

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• 作者：Weizhi NieAuthor Vitae ; Anan Liu ; ^{anan0422@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Zhongyang WangAuthor Vitae ; Yuting SuAuthor Vitae
• 关键词：3D object detection ; Exemplar SVM ; 3D object dataset ; Tracking
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：26 November 2016
• 年：2016
• 卷：215
• 期：Complete
• 页码：63-70
• 全文大小：1858 K

文摘

In recent years, the understanding the semantics of 3D scenes has been a wide interesting researching point in many application. However, 3D scenes detection remains many problems, due to the difficulty in acquiring sufficient 3D model towards training effective classifiers. In order to address these problems, in this paper, we first publish a new real-world 3D model dataset MV-RED, which includes 505 objects recoded by Kinect camera. Then we propose a novel 3D object detection approach in real-world scenes combined RGB image based on MV-RED dataset. In order to improve the detection precision, we also utilize the tracking method to improve the detection results. Finally, we evaluate our approach on the RGB-D dataset which is provided by Lai et al. (2012) pan id="bbib20">[20]pan>, achieving much greater efficiency and comparable accuracy. Our approach shows further major gains in accuracy when the training data from the target scenes is used, outperforming state-of-the-art approaches with far better efficiency.