A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach
Methods dealing with the problem of Joint Tracking and Classification (JTC) are abundant, among which Simultaneous Tracking and Classification (STC) provides a modularized scheme solving tracking and classification subproblems simultaneously. However, there is no explicit hard decision on the class...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-02-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/2/622 |
| _version_ | 1811279132774891520 |
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| author | Wen Cao Meng Hui Qisheng Wu |
| author_facet | Wen Cao Meng Hui Qisheng Wu |
| author_sort | Wen Cao |
| collection | DOAJ |
| description | Methods dealing with the problem of Joint Tracking and Classification (JTC) are abundant, among which Simultaneous Tracking and Classification (STC) provides a modularized scheme solving tracking and classification subproblems simultaneously. However, there is no explicit hard decision on the class label but only soft decision (class probability) is provided. This does not fit many practical cases, in which a hard decision is urgently needed. To solve this problem, this paper proposes a Hard decision-based STC (HSTC) method. HSTC takes all the decision error rate, timeliness, and estimation error into account. Specifically, for decision, the sequential probability ratio test is adopted due to its nice properties and also the adaptability to our situation. For estimation, by utilizing the two-way information exchange between the tracker and the classifier, we propose flexible three tracking schemes related to decision. The HSTC tracking result is divided into three parts according to the time of making the hard decision. In general, the proposed HSTC method takes advantage of both SPRT and STC. Finally, two illustrative JTC examples with hard decision verify the effectiveness of the the proposed HSTC method. They show that HSTC can meet the demand of the problem, and also has the performance superiority in both decision and estimation. |
| first_indexed | 2024-04-13T00:49:17Z |
| format | Article |
| id | doaj.art-d2244bb66cac4108bb3e06f1dcc83bee |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:49:17Z |
| publishDate | 2018-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d2244bb66cac4108bb3e06f1dcc83bee2022-12-22T03:09:55ZengMDPI AGSensors1424-82202018-02-0118262210.3390/s18020622s18020622A Novel Hard Decision Based Simultaneous Target Tracking and Classification ApproachWen Cao0Meng Hui1Qisheng Wu2School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Electronics and Control Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Electronics and Control Engineering, Chang’an University, Xi’an 710064, ChinaMethods dealing with the problem of Joint Tracking and Classification (JTC) are abundant, among which Simultaneous Tracking and Classification (STC) provides a modularized scheme solving tracking and classification subproblems simultaneously. However, there is no explicit hard decision on the class label but only soft decision (class probability) is provided. This does not fit many practical cases, in which a hard decision is urgently needed. To solve this problem, this paper proposes a Hard decision-based STC (HSTC) method. HSTC takes all the decision error rate, timeliness, and estimation error into account. Specifically, for decision, the sequential probability ratio test is adopted due to its nice properties and also the adaptability to our situation. For estimation, by utilizing the two-way information exchange between the tracker and the classifier, we propose flexible three tracking schemes related to decision. The HSTC tracking result is divided into three parts according to the time of making the hard decision. In general, the proposed HSTC method takes advantage of both SPRT and STC. Finally, two illustrative JTC examples with hard decision verify the effectiveness of the the proposed HSTC method. They show that HSTC can meet the demand of the problem, and also has the performance superiority in both decision and estimation.http://www.mdpi.com/1424-8220/18/2/622simultaneous tracking and classificationjoint target tracking and classificationhard decisionsequential probability ratio test |
| spellingShingle | Wen Cao Meng Hui Qisheng Wu A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach Sensors simultaneous tracking and classification joint target tracking and classification hard decision sequential probability ratio test |
| title | A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach |
| title_full | A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach |
| title_fullStr | A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach |
| title_full_unstemmed | A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach |
| title_short | A Novel Hard Decision Based Simultaneous Target Tracking and Classification Approach |
| title_sort | novel hard decision based simultaneous target tracking and classification approach |
| topic | simultaneous tracking and classification joint target tracking and classification hard decision sequential probability ratio test |
| url | http://www.mdpi.com/1424-8220/18/2/622 |
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