An Improved Face Recognition System for Service Robot Using Stereo Vision

Budiharto, Widodo; Santoso, Ari; Purwanto, Djoko; Jazidie, Achmad

doi:10.5772/17993

Cited by 9 publications

(9 citation statements)

References 18 publications

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“…The success rate using PCA in our proposed method and ITS face database is 95.5 %, higher than ATT face database 95.4% execution time, it seems the Indian face database (IFD) is shortest because the size of each image is lowest then ITS and ATT (b) [13] (b)…”

Section: Issn: 1693-6930mentioning

confidence: 85%

“…face. Each set of ITS face database consists of 3 poses (front, left, right ) and varied with illumination [13]. …”

Section: Improved Face Recognition Systemmentioning

confidence: 99%

“…Each of face database consists of 10 sets of people's face. Each set of ITS face database consists of 3 poses (front, left, right ) and varied with (a) (b) (c) ITS, Indian and ATT face database used as comparison to see the effect of illumination at face recognition [13].…”

Section: Ace Recognition Systemmentioning

confidence: 99%

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Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

et al. 2011

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Section: Issn: 1693-6930mentioning

confidence: 85%

“…face. Each set of ITS face database consists of 3 poses (front, left, right ) and varied with illumination [13]. …”

Section: Improved Face Recognition Systemmentioning

confidence: 99%

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Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

et al. 2011

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“…We have developed ITS face database consists of 3 poses (front, left, right ) and varied with illumination with total 12 images per people. For testing the database, we use 12 images randomly with variation of illumination generated by our program [8] [9]. Fig.…”

Section: Improved Face Recognition Systemmentioning

confidence: 99%

Multiple Moving Obstacles Avoidance for Humanoid Service Robot Using Stereo Vision  and Bayesian Approach

Budiharto

Rachmawati

2012

2012 Sixth Asia Modelling Symposium

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In this paper, we propose a robust multiple moving obstacles avoidance strategy using stereo vision for Humanoid Robot in indoor environment. We assume that this model of humanoid robot is used as a service robot to deliver a cup to customer from starting point to the destination. We have developed and introduced successfully three main modules to recognize faces, to identify obstacles and to maneuver. A group of people who are walking will be tracked as multiple moving obstacles. Predefined maneuver to avoid obstacles applied to robot because the limitation of view angle from stereo camera to detect obstacles. The contribution of this research is a new method for multiple moving obstacle avoidance strategy with Bayesian approach using stereo vision based on the direction and speed of obstacles. We present the results of the experiment of the humanoid robot called Gatotkoco II which uses our proposed method and we also evaluate its performance. The proposed moving obstacles avoidance strategy was tested empirically and proven effective for humanoid robot.

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“…With the group of eye-to-hand camera system, the system is also tracking target very well, even when the target and the robot move [7] or mobile obstructions appear on the way [2]. images, the image velocity [8] can be estimated to track the target by using classical controller.…”

Section: Introductionmentioning

confidence: 99%

A new control method for stereo visual servoing system with Pan-tilt platform

Chung¹,

Cát²

2015

JCC

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This paper proposes a new control method for Pan-Tilt stereo camera system to track a moving object when there are many uncertainties in the parameters of both camera and Pan-Tilt platform. If a pair of cameras placed on the Pan-Tilt robot, it is unnecessary for its installation location to be determined accurately. Assuming that the optical parameters like focal length of two cameras in the simulation are the same. A two degree of freedom Pan-Tilt platform holding camera has many uncertain parameters such as inertial moment, Jacobian matrix, the friction and noise impact, etc. The proposed control algorithm is highly adaptive and robust due to the use of a compensating neural network with on-line learning rule. The asymptotic stability of overall control system is proved by Lyapunov's stability method.

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An Improved Face Recognition System for Service Robot Using Stereo Vision

Cited by 9 publications

References 18 publications

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Multiple Moving Obstacles Avoidance for Humanoid Service Robot Using Stereo Vision  and Bayesian Approach

A new control method for stereo visual servoing system with Pan-tilt platform

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An Improved Face Recognition System for Service Robot Using Stereo Vision

Cited by 9 publications

References 18 publications

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Multiple Moving Obstacles Avoidance for Humanoid Service Robot Using Stereo Vision&#x0A0;&#x0A0;and Bayesian Approach

A new control method for stereo visual servoing system with Pan-tilt platform

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Multiple Moving Obstacles Avoidance for Humanoid Service Robot Using Stereo Vision and Bayesian Approach