Title :
Simultaneous object extraction and disparity estimation using stochastic diffusion
Author :
Lee, Sang Hwa ; Cho, Nam Ik ; Kanatsugu, Yasuaki ; Park, Jong-ji
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ., South Korea
Abstract :
This paper proposes a Bayesian maximum a posteriori (MAP) method to estimate disparity field and to extract objects in the stereoscopic images. The disparity and segmentation fields are modelled as the Markov random fields (MRFs), and are estimated by a stochastic approach called stochastic diffusion. The stochastic diffusion is a new energy minimization method to search for the solution fields in the MAP estimation. A clustering method utilizes the disparity field and color information to classify the regions into foreground objects or background. The line field is also included to improve the detection of the object boundaries. According to the some experiments, the proposed approach shows good performances in the foreground objects extraction even in the complex background.
Keywords :
Markov processes; feature extraction; image colour analysis; image segmentation; maximum likelihood estimation; object detection; stereo image processing; Bayesian maximum a posteriori; Markov random fields; clustering method; disparity estimation; image segmentation; object extraction; stereoscopic images; stochastic diffusion; Bayesian methods; Broadcasting; Computer science; Data mining; Image segmentation; Markov random fields; Motion estimation; Random variables; Stochastic processes; Stochastic systems;
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7803-7750-8
DOI :
10.1109/ICIP.2003.1247280