Title :
Recognizing multiple overlapping objects in image: an optimal formulation
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
fDate :
2/1/2000 12:00:00 AM
Abstract :
A statistically optimal formulation is presented for recognizing multiple, partially occluded objects. The optimality, in terms of the maximum a posteriori (MAP) principle, is with respect to all, rather than just individual modeled objects. Various constraints are incorporated into the posterior distribution, a two-stage MAP estimation approach is proposed to reduce the computational cost
Keywords :
computational complexity; image recognition; maximum likelihood estimation; object recognition; MAP principle; computational cost; maximum a posteriori principle; multiple overlapping objects; optimal formulation; partially occluded objects; posterior distribution; statistically optimal formulation; two-stage MAP estimation approach; Computational efficiency; Data mining; Feature extraction; Image recognition; Layout; Markov random fields; Object recognition; Object segmentation; Statistics; Uncertainty;
Journal_Title :
Image Processing, IEEE Transactions on
