tailieunhanh - Báo cáo hóa học: "A Probabilistic Model for Face Transformation with Application to Person Identification"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A Probabilistic Model for Face Transformation with Application to Person Identification | EURASIP Journal on Applied Signal Processing 2004 4 510-521 2004 Hindawi Publishing Corporation A Probabilistic Model for Face Transformation with Application to Person Identification Florent Perronnin Multimedia Communications Department Institut Eurécom BP 193 06904 Sophia Antipolis Cedex France Email perronni@ Jean-Luc Dugelay Multimedia Communications Department Institut Eurécom BP 193 06904 Sophia Antipolis Cedex France Email dugelay@ Kenneth Rose Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106-9560 USA Em ail rose@ece. u csb. edu Received 30 October 2002 Revised 23 June 2003 A novel approach for content-based image retrieval and its specialization to face recognition are described. While most face recognition techniques aim at modeling faces our goal is to model the transformation between face images of the same person. As a global face transformation may be too complex to be modeled directly it is approximated by a collection of local transformations with a constraint that imposes consistency between neighboring transformations. Local transformations and neighborhood constraints are embedded within a probabilistic framework using two-dimensional hidden Markov models 2D HMMs . We further introduce a new efficient technique called turbo-HMM T-HMM for approximating intractable 2D HMMs. Experimental results on a face identification task show that our novel approach compares favorably to the popular eigenfaces and fisherfaces algorithms. Keywords and phrases face recognition image indexing face transformation hidden Markov models. 1. INTRODUCTION Pattern classification is concerned with the general problem of inferring classes or categories from observations 1 . The success of a pattern classification system is largely dependent on the quality of its stochastic model which generally models the generation of observations to capture the intraclass variability. Face recognition is a challenging .

TÀI LIỆU LIÊN QUAN
crossorigin="anonymous">
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.