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Batch mode adaptive multiple instance learning for computer vision tasks

หน่วยงาน Nanyang Technological University, Singapore

รายละเอียด

ชื่อเรื่อง : Batch mode adaptive multiple instance learning for computer vision tasks
นักวิจัย : Li, Wen , Duan, Lixin , Tsang, Ivor Wai-Hung , Xu, Dong
คำค้น : DRNTU::Engineering::Computer science and engineering.
หน่วยงาน : Nanyang Technological University, Singapore
ผู้ร่วมงาน : -
ปีพิมพ์ : 2555
อ้างอิง : Li, W., Duan, L., Tsang, I. W.-H., & Xu, D. (2012). Batch Mode Adaptive Multiple Instance Learning for Computer Vision Tasks. 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2368-2375. , http://hdl.handle.net/10220/12473 , http://dx.doi.org/10.1109/CVPR.2012.6247949
ที่มา : -
ความเชี่ยวชาญ : -
ความสัมพันธ์ : -
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance labels in positive bags, the training process of traditional MIL methods is usually computationally expensive, which limits the applications of MIL in more computer vision tasks. In this paper, we propose a novel batch mode framework, namely Batch mode Adaptive Multiple Instance Learning (BAMIL), to accelerate the instance-level MIL methods. Specifically, instead of using all training bags at once, we divide the training bags into several sets of bags (i.e., batches). At each time, we use one batch of training bags to train a new classifier which is adapted from the latest pre-learned classifier. Such batch mode framework significantly accelerates the traditional MIL methods for large scale applications and can be also used in dynamic environments such as object tracking. The experimental results show that our BAMIL is much faster than the recently developed MIL with constrained positive bags while achieves comparable performance for text-based web image retrieval. In dynamic settings, BAMIL also achieves the better overall performance for object tracking when compared with other online MIL methods.

บรรณานุกรม :
Li, Wen , Duan, Lixin , Tsang, Ivor Wai-Hung , Xu, Dong . (2555). Batch mode adaptive multiple instance learning for computer vision tasks.
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Li, Wen , Duan, Lixin , Tsang, Ivor Wai-Hung , Xu, Dong . 2555. "Batch mode adaptive multiple instance learning for computer vision tasks".
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Li, Wen , Duan, Lixin , Tsang, Ivor Wai-Hung , Xu, Dong . "Batch mode adaptive multiple instance learning for computer vision tasks."
    กรุงเทพมหานคร : Nanyang Technological University, Singapore, 2555. Print.
Li, Wen , Duan, Lixin , Tsang, Ivor Wai-Hung , Xu, Dong . Batch mode adaptive multiple instance learning for computer vision tasks. กรุงเทพมหานคร : Nanyang Technological University, Singapore; 2555.