scholarly journals Face Detection of Video Image Sequence Based on Human Characteristics

2015 ◽  
Vol 7 (1) ◽  
pp. 2029-2038
Author(s):  
Yansong Liu ◽  
Yaopei Zhao ◽  
Zhenqiang Mi
Keyword(s):  
Face Detection ◽  
Image Sequence ◽  
Video Image

Real Time 3D Location of a Car from Three Characteristic Points Observed in a Video Image Sequence

1994 ◽  
Vol 27 (12) ◽  
pp. 361-366
Author(s):  
E. Montagne ◽  
J. Alizon ◽  
P. Martinet ◽  
J. Gallice
Keyword(s):  
Real Time ◽  
Image Sequence ◽  
Video Image ◽  
Characteristic Points

Face Tracking

2011 ◽  
pp. 92-162
Author(s):  
Daijin Kim ◽  
Jaewon Sung
Keyword(s):  
Face Detection ◽  
Image Sequence ◽  
Face Tracking ◽  
Detection Methods ◽  
Continuous Change ◽  
Image Frame ◽  
The Face ◽  
Previous Image

When we want to analyze the continuous change of the face in an image sequence, applying face tracking methods is a better choice than applying the face detection methods to each image frame. Usually, the face tracking methods are more efficient than the ordinary face detection methods because they can utilize the trajectory of the face in the previous image frames with an assumption that the shape, texture, or motion of the face change smoothly. There have been many approaches to face tracking. We divide the face tracking methods into several categories according to the cues that are extracted for tracking.

Research of Video Surveillance System Base on Face Recognition and Motion Detection

2011 ◽  
Vol 271-273 ◽  
pp. 961-966
Author(s):  
Da Guang Jiang ◽  
Jun Kai Yi ◽  
Gao Hui Bian
Keyword(s):  
Face Detection ◽  
Motion Detection ◽  
Surveillance System ◽  
Skin Color ◽  
Moving Objects ◽  
Image Sequence ◽  
Detection Algorithm ◽  
Improved Method ◽  
Face Area ◽  
Slow Moving

In this paper, by using skin-color feature, especial location and pixel features of eyes in face area, an efficient face detection algorithm was designed. After face detection, discrete cosine Transform (DCT) was used to extract a set of observation, which is provided to train and recognize faces in the way of Hidden Markov Model (HMM). In order to solve the shortcoming that traditional motion detection algorithm can not be used to detect slow moving objects from an image sequence, an improved method was proposed by rebuilding the background.

Automatic eye tracking in video image sequence

2001 ◽  
Author(s):  
Kai Qian ◽  
GuoWei Zhou ◽  
Chih-Cheng Hung ◽  
Prabir Bhattacharya ◽  
Jigang Liu
Keyword(s):  
Eye Tracking ◽  
Image Sequence ◽  
Video Image
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