| Hybrid incremental learning of new data and new classes for hand-held object recognition | |
| Chen, Chengpeng1,4; Min, Weiqing2,3; Li, Xue2; Jiang, Shuqiang2,4 | |
| Corresponding Author | Jiang, Shuqiang(sqjiang@ict.ac.cn) |
| 2019 | |
| Source Publication | JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
 |
| ISSN | 1047-3203 |
| Volume | 58Pages:138-148 |
| Abstract | Intelligence technology is an important research area. As a very special yet important case of object recognition, hand-held object recognition plays an important role in intelligence technology for its many applications such as visual question-answering and reasoning. In real-world scenarios, the datasets are open-ended and dynamic: new object samples and new object classes increase continuously. This requires the intelligence technology to enable hybrid incremental learning, which supports both data-incremental and class-incremental learning to efficiently learn the new information. However, existing work mainly focuses on one side of incremental learning, either data-incremental or class-incremental learning while do not handle two sides of incremental learning in a unified framework. To solve the problem, we present a Hybrid Incremental Learning (HIL) method based on Support Vector Machine (SVM), which can incrementally improve its recognition ability by learning new object samples and new object concepts during the interaction with humans. In order to integrate data-incremental and class-incremental learning into one unified framework, HIL adds the new classification-planes and adjusts existing classification-planes under the setting of SVM. As a result, our system can simultaneously improve the recognition quality of known concepts by minimizing the prediction error and transfer the previous model to recognize unknown objects. We apply the proposed method into hand-held object recognition and the experimental results demonstrated its advantage of HIL. In addition, we conducted extensive experiments on the subset of ImageNet and the experimental results further validated the effectiveness of the proposed method. (C) 2018 Elsevier Inc. All rights reserved. |
| Keyword | Incremental learning Object recognition SVM Human-machine interaction |
| Funding Organization | Beijing Natural Science Foundation ; National Natural Science Foundation of China ; Lenovo Outstanding Young Scientists Program ; National Program for Special Support of Eminent Professionals ; National Program for Support of Top-notch Young Professionals ; China Postdoctoral Science Foundation ; State Key Laboratory of Robotics |
| DOI | 10.1016/j.jvcir.2018.11.009 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | Beijing Natural Science Foundation[4174106] ; National Natural Science Foundation of China[61532018] ; National Natural Science Foundation of China[61602437] ; Lenovo Outstanding Young Scientists Program ; National Program for Special Support of Eminent Professionals ; National Program for Support of Top-notch Young Professionals ; China Postdoctoral Science Foundation[2017T100110] ; State Key Laboratory of Robotics |
| WOS Research Area | Computer Science |
| WOS Subject | Computer Science, Information Systems ; Computer Science, Software Engineering |
| WOS ID | WOS:000457668100015 |
| Publisher | ACADEMIC PRESS INC ELSEVIER SCIENCE |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/131750 |
| Collection | 中国科学院金属研究所 |
| Corresponding Author | Jiang, Shuqiang |
| Affiliation | 1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 3.Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang, Liaoning, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | Chen, Chengpeng,Min, Weiqing,Li, Xue,et al. Hybrid incremental learning of new data and new classes for hand-held object recognition[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2019,58:138-148. |
| APA | Chen, Chengpeng,Min, Weiqing,Li, Xue,&Jiang, Shuqiang.(2019).Hybrid incremental learning of new data and new classes for hand-held object recognition.JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,58,138-148. |
| MLA | Chen, Chengpeng,et al."Hybrid incremental learning of new data and new classes for hand-held object recognition".JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 58(2019):138-148. |
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