TY - JOUR
T1 - Performance Analysis of Fuzzy-Weighted Multiple Instance Learning on Thermal Video-Based Visual Tracking
AU - Ibrahim, Nur
AU - Darlis, Arsyad R.
AU - Kusumoputro, Benyamin
N1 - Publisher Copyright:
© 2022 Journal of Image and Graphics.
PY - 2022/6
Y1 - 2022/6
N2 - In this paper, performance analysis of fuzzy-Weighted Multiple Instance Learning (WMIL) with the fuzzy logic tracker on thermal video-based visual tracking is presented. Thermal cameras have been used recently in some pedestrian areas, cars, and surveillance areas that need to be monitored all day. A thermal camera with advantages over the other visual-based sensors in low-light conditions is utilized in this research. The paper presents an analysis of visual tracking with an experimental method in the low-light outdoor environment. The thermal camera is used to record object movement used as video sequences to analyze the performance of our proposed system that integrate Type-2 Fuzzy Logic System (T2FLS) and WMIL tracker. The WMIL-T2FLS tracker performance is shown in the failure rate and center location error. The results show that the object in the thermal video sequences can be tracked using WMIL-T2FLS tracker in the low-light outdoor environment with a low level of failure rate and center location error. Then, the WMIL-T2FLS tracker can track the object when it occluded with the other similar object quite accurately. This result was compared with the original WMIL and some state-of-the art of tracking algorithm: DSST, ECO, KCF, SRDCF, and BACF. The research results showed that the WMIL-T2FLS system significantly improved compared with the WMIL method only, with a success rate improvement of at least 35 % and precision of at least 0.2 in 15 m dan 10 m. WMIL-T2FLS tracker also outperform some state-of-the art method and showed good performance in visual tracking at low-light environments.
AB - In this paper, performance analysis of fuzzy-Weighted Multiple Instance Learning (WMIL) with the fuzzy logic tracker on thermal video-based visual tracking is presented. Thermal cameras have been used recently in some pedestrian areas, cars, and surveillance areas that need to be monitored all day. A thermal camera with advantages over the other visual-based sensors in low-light conditions is utilized in this research. The paper presents an analysis of visual tracking with an experimental method in the low-light outdoor environment. The thermal camera is used to record object movement used as video sequences to analyze the performance of our proposed system that integrate Type-2 Fuzzy Logic System (T2FLS) and WMIL tracker. The WMIL-T2FLS tracker performance is shown in the failure rate and center location error. The results show that the object in the thermal video sequences can be tracked using WMIL-T2FLS tracker in the low-light outdoor environment with a low level of failure rate and center location error. Then, the WMIL-T2FLS tracker can track the object when it occluded with the other similar object quite accurately. This result was compared with the original WMIL and some state-of-the art of tracking algorithm: DSST, ECO, KCF, SRDCF, and BACF. The research results showed that the WMIL-T2FLS system significantly improved compared with the WMIL method only, with a success rate improvement of at least 35 % and precision of at least 0.2 in 15 m dan 10 m. WMIL-T2FLS tracker also outperform some state-of-the art method and showed good performance in visual tracking at low-light environments.
KW - low-light outdoor environment
KW - thermal camera
KW - type-2 fuzzy logic system
KW - visual tracking
KW - weighted multiple instance learning
UR - http://www.scopus.com/inward/record.url?scp=85130048706&partnerID=8YFLogxK
U2 - 10.18178/joig.10.2.88-94
DO - 10.18178/joig.10.2.88-94
M3 - Article
AN - SCOPUS:85130048706
SN - 2301-3699
VL - 10
SP - 88
EP - 94
JO - Journal of Image and Graphics(United Kingdom)
JF - Journal of Image and Graphics(United Kingdom)
IS - 2
ER -