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Optical Engineering

Object of interest extraction in low-frame-rate image sequences and application to mobile mapping systems
Author(s): Peng Li; Cheng Wang
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Paper Abstract

Here, we present a novel object of interest (OOI) extraction framework designed for low-frame-rate (LFR) image sequences, typically from mobile mapping systems (MMS). The proposed method integrates tracking and segmentation in a unified framework. We propose a novel object-shaped kernel-based scale-invariant mean shift algorithm to track the OOI through the LFR sequences and keep the temporal consistency. Then the well-known GrabCut approach for static image segmentation is generalized to the LFR sequences. We analyze the imaging geometry of the OOI in LFR sequences collected by the MMS and design a Kalman filter module to assist the proposed tracker. Extensive experimental results on real LFR sequences collected by VISAT™ MMS demonstrate that the proposed approach is robust to the challenges such as low frame rate, fast scaling, and large inter-frame displacement of the OOI.

Paper Details

Date Published: 5 June 2012
PDF: 13 pages
Opt. Eng. 51(6) 067201 doi: 10.1117/1.OE.51.6.067201
Published in: Optical Engineering Volume 51, Issue 6
Show Author Affiliations
Peng Li, National Univ. of Defense Technology (China)
Cheng Wang, Xiamen Univ. (China)


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