Robust Target Model Update for Mean-shift Tracking with Background Weighted Histogram

Autor: Yoo-Joo Choi, Ku-Jin Kim, Jung-Keun Suh, Yong-Hyun Jang
Rok vydání: 2016
Předmět:
Zdroj: KSII Transactions on Internet and Information Systems. 10
ISSN: 1976-7277
DOI: 10.3837/tiis.2016.03.025
Popis: This paper presents a target model update scheme for the mean-shift tracking with background weighted histogram. In the scheme, the target candidate histogram is corrected by considering the back-projection weight of each pixel in the kernel after the best target candidate in the current frame image is chosen. In each frame, the target model is updated by the weighted average of the current target model and the corrected target candidate. We compared our target model update scheme with the previous ones by applying several test sequences. The experimental results showed that the object tracking accuracy was greatly improved by using the proposed scheme.
Databáze: OpenAIRE