Estimating Human Body and Head Orientation Change to Detect Visual Attention Direction

被引:0
作者
Ozturk, Ovgu
Yamasaki, Toshihiko
Aizawa, Kiyoharu
机构
来源
COMPUTER VISION - ACCV 2010 WORKSHOPS, PT I | 2011年 / 6468卷
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a method to estimate human body and head orientation change around yaw axis from low-resolution data. Body orientation is calculated by using Shape Context algorithm to match the outline of upper body with predefined shape templates within the ranges of 22.5 degrees. Then, motion flow vectors of SIFT features around head region are utilized to estimate the change in head orientation. Body orientation change and head orientation change can be added to the initial orientation to compute the new visual focus of attention of the person. Experimental results are presented to prove the effectiveness of the proposed method. Successful estimations, which are supported by a user study, were obtained from low-resolution data under various head pose articulations.
引用
收藏
页码:410 / 419
页数:10
相关论文
共 22 条
[1]  
[Anonymous], 1981, IJCAI
[2]  
Ba S., 2010, IEEE T PATTERN ANAL, V99
[3]   SURF: Speeded up robust features [J].
Bay, Herbert ;
Tuytelaars, Tinne ;
Van Gool, Luc .
COMPUTER VISION - ECCV 2006 , PT 1, PROCEEDINGS, 2006, 3951 :404-417
[4]   Shape matching and object recognition using shape contexts [J].
Belongie, S ;
Malik, J ;
Puzicha, J .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (04) :509-522
[5]  
Benfold B., 2008, BMVC
[6]  
Brown L.M., 2002, Comparative study of coarse head pose estimation
[7]  
Chutorian E. M., 2009, IEEE T PATTERN ANAL, V31
[8]  
Gandhi T, 2008, IEEE INT VEH SYM, P795
[9]  
Glas DF, 2007, 2007 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-9, P608
[10]   Distinctive image features from scale-invariant keypoints [J].
Lowe, DG .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2004, 60 (02) :91-110