TY - GEN
T1 - Comparison of correlation filter-based visual tracker for human guide tracking in smart wheelchair
AU - Utaminingrum, Fitri
AU - Kabisat, Aldiansyah Satrio
AU - Larasati, Anindya Zulva
AU - Mufita, Aulia Riza
AU - Al Huda, Fais
AU - Arwan, Achmad
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2026/4/7
Y1 - 2026/4/7
N2 - Wheelchairs are vital mobility aids, yet existing control interfaces remain inadequate for users with severe disabilities who cannot operate them independently. Visual tracking-based human-following systems offer a promising solution, but correlation filter-based trackers (CFTs) have not been systematically evaluated in this context. This study compares four representative CFT algorithms - Minimum Output Sum of Squared Error (MOSSE), Kernelized Correlation Filter (KCF), Channel and Spatial Reliability Tracking (CSRT), and Efficient Convolution Operator (ECO) - for human-guide tracking in smart wheelchair navigation. Using 20 annotated video sequences comprising 24,648 frames under diverse conditions such as appearance variation, low light, occlusion, and similar-object interference, performance was assessed using precision, normalized precision, and success rate. Results show that ECO achieved the best overall performance with precision 0.4328, normalized precision 0.7645, and success rate 0.7302 at 30 FPS, outperforming CSRT, KCF, and MOSSE. These findings imply that ECO-based human-following systems can enhance safety, reduce caregiver burden, and support practical deployment in assistive mobility technologies.
AB - Wheelchairs are vital mobility aids, yet existing control interfaces remain inadequate for users with severe disabilities who cannot operate them independently. Visual tracking-based human-following systems offer a promising solution, but correlation filter-based trackers (CFTs) have not been systematically evaluated in this context. This study compares four representative CFT algorithms - Minimum Output Sum of Squared Error (MOSSE), Kernelized Correlation Filter (KCF), Channel and Spatial Reliability Tracking (CSRT), and Efficient Convolution Operator (ECO) - for human-guide tracking in smart wheelchair navigation. Using 20 annotated video sequences comprising 24,648 frames under diverse conditions such as appearance variation, low light, occlusion, and similar-object interference, performance was assessed using precision, normalized precision, and success rate. Results show that ECO achieved the best overall performance with precision 0.4328, normalized precision 0.7645, and success rate 0.7302 at 30 FPS, outperforming CSRT, KCF, and MOSSE. These findings imply that ECO-based human-following systems can enhance safety, reduce caregiver burden, and support practical deployment in assistive mobility technologies.
KW - assistive mobility
KW - correlation filter based tracker
KW - human-following
KW - smart wheelchair
KW - visual tracking
UR - https://www.scopus.com/pages/publications/105040271363
U2 - 10.1117/12.3110753
DO - 10.1117/12.3110753
M3 - Conference contribution
AN - SCOPUS:105040271363
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Eighth International Conference on Image Processing and Machine Vision, IPMV 2026
A2 - Zhang, Hui
PB - SPIE
T2 - 8th International Conference on Image Processing and Machine Vision, IPMV 2026
Y2 - 10 January 2026 through 12 January 2026
ER -