ADAPTIVE VISUAL TARGET DETECTION AND TRACKING USING INCREMENTAL APPEARANCE LEARNING

被引：0

作者：

Yazdian-Dehkordi, Mandi ^{[1
]}

Azimifar, Zohreh ^{[1
]}

机构：

[1] Shiraz Univ, Sch Elect & Comp Engn, CVPR Lab, Shiraz, Iran

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2015年

关键词：

Tracking; Incremental appearance learning; Keypoint-based Model; ENTROPY DISTRIBUTION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Multiple visual target tracking is a challenging problem due to various uncertainties including noise, clutter, miss-detection and occlusion. In this paper, we propose an adaptive keypoint-based appearance model to represent the appearance of visual targets independent of their shape or type. We also develop an incremental learning algorithm to learn the appearance of targets in time. The proposed method utilizes a simple background subtraction method to prune insignificant keypoints and to adapt the target appearances in different frames. The experimental results presented on several video datasets show the effectiveness of our proposed method.

引用

页码：1041 / 1045

页数：5

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