5 June 2012 Object of interest extraction in low-frame-rate image sequences and application to mobile mapping systems
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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.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Peng Li, Cheng Wang, "Object of interest extraction in low-frame-rate image sequences and application to mobile mapping systems," Optical Engineering 51(6), 067201 (5 June 2012). https://doi.org/10.1117/1.OE.51.6.067201 . Submission:
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