Real-Time Face Tracking and Recognition Based on Particle Filtering and AdaBoosting Techniques

In recent times face tracking and face recognition have turned out to be increasingly dynamic research field in image processing. This work proposed the framework DEtecting Contiguous Outliers in the LOw-rank Representation for face tracking, in this algorithm the background is assessed by a low-rank network and foreground articles can be distinguished as anomalies. This is suitable for non-rigid foreground motion and moving camera. The face of a foreground person is caught from the frame and then it is contrasted and the speculated pictures stored in the dataset. Here we used Viola-Jones algorithm for face recognition. This approach outperforms the traditional algorithms on multimodal video methodologies and it works adequately on extensive variety of security and surveillance purposes. Results on the continuous demonstrate that the proposed calculation can correctly obtain facial features points. The algorithm is relegate on the continuous camera input and under ongoing ecological conditions.

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Real-Time Face Tracking and Recognition System Using Kanade-Lucas-Tomasi and Two-Dimensional Principal Component Analysis

2018 International Conference on Advanced Science and Engineering (ICOASE) ◽

10.1109/icoase.2018.8548818 ◽

2018 ◽

Author(s):

Nawaf Hazim Barnouti ◽

Mohanad Hazim Nsaif Al-Mayyahi ◽

Sinan Sameer Mahmood Al-Dabbagh

Keyword(s):

Principal Component Analysis ◽

Real Time ◽

Principal Component ◽

Component Analysis ◽

Recognition System ◽

Face Tracking ◽

Two Dimensional ◽

Tracking And Recognition

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A robust and real-time algorithm for human face tracking using improved particle filtering

2009 Chinese Control and Decision Conference ◽

10.1109/ccdc.2009.5192921 ◽

2009 ◽

Cited By ~ 1

Author(s):

Qichang Duan ◽

Qi Zhou ◽

Pan Duan

Keyword(s):

Real Time ◽

Particle Filtering ◽

Time Algorithm ◽

Face Tracking ◽

Human Face

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Real-time face tracking and recognition by sparse eigentracker with associative mapping to 3D shape

Image and Vision Computing ◽

10.1016/j.imavis.2011.12.010 ◽

2012 ◽

Vol 30 (3) ◽

pp. 147-158 ◽

Cited By ~ 5

Author(s):

Yuki Oka ◽

Takeshi Shakunaga

Keyword(s):

Real Time ◽

Face Tracking ◽

3D Shape ◽

Tracking And Recognition

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Research on the Real-Time Multiple Face Detection, Tracking and Recognition Based on Video

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.373-375.442 ◽

2013 ◽

Vol 373-375 ◽

pp. 442-446

Author(s):

Hai Feng Sang ◽

Chao Xu ◽

Dan Yang Wu ◽

Jing Huang

Keyword(s):

Real Time ◽

Face Detection ◽

Recognition System ◽

Detection Algorithm ◽

Research Field ◽

Face Tracking ◽

Fusion Algorithm ◽

The Real ◽

Video Images ◽

Tracking And Recognition

The video images of human face tracking and recognition is a hot research field of biometric recognition and artificial intelligence in recent years. This paper presents an automatic face tracking and recognition system, which can track multiple faces real-timely and recognize the identity. Aiming at Adaboost face detection algorithm is easy to false detection, presents a fusion algorithm based on Adaboost face detection algorithm and Active Shape Model. The algorithm is not only detect face real-timely but also remove the non-face areas; A multi thread CamShift tracking algorithm is proposed for many faces interlaced and face number of changes in the scene . Meanwhile, the algorithm also can identify the faces which have been tracked in the video. The experiment results show that the system is capable of improving the accurate rate of faces detection and recognition in complex backgrounds, and furthermore it also can track the real-time faces effectively.

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