Abstract
High definition (HD) camera is widely used in surveillance systems. An HD camera with optical zoom is useful for monitoring a large area. However, it is inconvenient for a user to manually control the optical zoom for a long time. To exploit the functionality and extend the application domains of a HD camera, the zooming should be controlled automatically. Therefore, an automatic zooming mechanism is proposed in this paper. When the number of an object is small in the field of view (FOV) of the camera and an object is moving through the FOV, the zoom is controlled for capturing the object as clear as possible. A clear object image is useful for related image-based services, such as face recognition. In order to achieve the above goal, a Gaussian Mixture Model (GMM), temporal image differencing, a CamShift tracking method, and a Kalman filter are utilized for object detection and tracking. Then, an adaptive neuro-fuzzy inference system (ANFIS) is used to learn and determine a suitable value for adjusting the zoom. According to the experimental study of the prototype, the results show that the proposed mechanism is useful to capture the clear images of moving objects in a practical environment. A face detection algorithm is also used to demonstrate the feasibility of the captured clear images.
| Original language | English |
|---|---|
| Title of host publication | 19th International Conference on Advanced Communications Technology |
| Subtitle of host publication | Opening Era of Smart Society, ICACT 2017 - Proceeding |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 869-876 |
| Number of pages | 8 |
| ISBN (Electronic) | 9788996865094 |
| DOIs | |
| Publication status | Published - 2017 Mar 29 |
| Event | 19th International Conference on Advanced Communications Technology, ICACT 2017 - Pyeongchang, Korea, Republic of Duration: 2017 Feb 19 → 2017 Feb 22 |
Other
| Other | 19th International Conference on Advanced Communications Technology, ICACT 2017 |
|---|---|
| Country | Korea, Republic of |
| City | Pyeongchang |
| Period | 17-02-19 → 17-02-22 |
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
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Automatic zooming mechanism for capturing clear moving object image using high definition fixed camera. / Liao, Hsien Chou; Chen, Po Yueh; Lin, Zi Jun; Lim, Zi Yi.
19th International Conference on Advanced Communications Technology: Opening Era of Smart Society, ICACT 2017 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2017. p. 869-876 7890238.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Automatic zooming mechanism for capturing clear moving object image using high definition fixed camera
AU - Liao, Hsien Chou
AU - Chen, Po Yueh
AU - Lin, Zi Jun
AU - Lim, Zi Yi
PY - 2017/3/29
Y1 - 2017/3/29
N2 - High definition (HD) camera is widely used in surveillance systems. An HD camera with optical zoom is useful for monitoring a large area. However, it is inconvenient for a user to manually control the optical zoom for a long time. To exploit the functionality and extend the application domains of a HD camera, the zooming should be controlled automatically. Therefore, an automatic zooming mechanism is proposed in this paper. When the number of an object is small in the field of view (FOV) of the camera and an object is moving through the FOV, the zoom is controlled for capturing the object as clear as possible. A clear object image is useful for related image-based services, such as face recognition. In order to achieve the above goal, a Gaussian Mixture Model (GMM), temporal image differencing, a CamShift tracking method, and a Kalman filter are utilized for object detection and tracking. Then, an adaptive neuro-fuzzy inference system (ANFIS) is used to learn and determine a suitable value for adjusting the zoom. According to the experimental study of the prototype, the results show that the proposed mechanism is useful to capture the clear images of moving objects in a practical environment. A face detection algorithm is also used to demonstrate the feasibility of the captured clear images.
AB - High definition (HD) camera is widely used in surveillance systems. An HD camera with optical zoom is useful for monitoring a large area. However, it is inconvenient for a user to manually control the optical zoom for a long time. To exploit the functionality and extend the application domains of a HD camera, the zooming should be controlled automatically. Therefore, an automatic zooming mechanism is proposed in this paper. When the number of an object is small in the field of view (FOV) of the camera and an object is moving through the FOV, the zoom is controlled for capturing the object as clear as possible. A clear object image is useful for related image-based services, such as face recognition. In order to achieve the above goal, a Gaussian Mixture Model (GMM), temporal image differencing, a CamShift tracking method, and a Kalman filter are utilized for object detection and tracking. Then, an adaptive neuro-fuzzy inference system (ANFIS) is used to learn and determine a suitable value for adjusting the zoom. According to the experimental study of the prototype, the results show that the proposed mechanism is useful to capture the clear images of moving objects in a practical environment. A face detection algorithm is also used to demonstrate the feasibility of the captured clear images.
UR - http://www.scopus.com/inward/record.url?scp=85018512507&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018512507&partnerID=8YFLogxK
U2 - 10.23919/ICACT.2017.7890238
DO - 10.23919/ICACT.2017.7890238
M3 - Conference contribution
AN - SCOPUS:85018512507
SP - 869
EP - 876
BT - 19th International Conference on Advanced Communications Technology
PB - Institute of Electrical and Electronics Engineers Inc.
ER -