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Occluded and Low Resolution Face Detection with Hierarchical Deformable Model

원문정보

Xiong Yang, Gang Peng, Zhaoquan Cai, Kehan Zeng

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초록

영어

This paper presents a hierarchical deformable model for robust human face detection, especially with occlusions and under low resolution. By parsing, we mean inferring the parse tree (a configuration of the proposed hierarchical model) for each face instance. In modeling, a three-layer hierarchical model is built consisting of six nodes. For each node, an active basis model is trained, and their spatial relations such as relative locations and scales are modeled using Gaussian distributions. In computing, we run the learned active basis models on testing images to obtain bottom-up hypotheses, followed by explicitly testing the compatible relations among those hypotheses to do verification and construct the parse tree in a top-down manner. In experiments, we test our approach on CMU+MIT face test set with improved performance obtained.

목차

Abstract
 I. INTRODUCTION
 II. GRAPH MODEL FOR FACE IN HIERARCHY
 III. ACTIVE BASIS MODEL
 IV. PROBLEM FORMULATION
 V. TWO COMPUTING PROCESSES IN HIERARCHICAL MODEL
 VI. EXPERIMENTAL PROCEDURE AND RESULTS
 REFERENCES

저자정보

  • Xiong Yang Dept. of Computer Science Huizhou University Huizhou, China
  • Gang Peng Dept. of Computer Science Huizhou University Huizhou, China
  • Zhaoquan Cai Dept. of Computer Science Huizhou University Huizhou, China
  • Kehan Zeng Dept. of Computer Science Huizhou University Huizhou, China

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자료제공 : 네이버학술정보

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