Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor’s body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

A low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands is presented. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results using only red markers for controlling the robot's movements.

A low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands is presented. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results using only red markers for controlling the robot's movements.

Human-robot interaction is an evolving area of research in the past few years. Human-robot interaction deals with how humans can interact with, send data to, or receive data from robots. One of the major obstacles in this field is how the robot can obtain the depth information of the surrounding objects. Few years ago, Microsoft has released a depth sensor that computes the depth information using IR rays. Many researches are conducted to control robots using depth sensors, such as Microsoft Kinect and Asus Xition. Although depth sensors are considered to be low cost, it may be unavailable for many users. In this work, we develop a low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results compared to those provided by depth sensors.

Human-robot interaction is an evolving area of research in the past few years. Human-robot interaction deals with how humans can interact with, send data to, or receive data from robots. One of the major obstacles in this field is how the robot can obtain the depth information of the surrounding objects. Few years ago, Microsoft has released a depth sensor that computes the depth information using IR rays. Many researches are conducted to control robots using depth sensors, such as Microsoft Kinect and Asus Xition. Although depth sensors are considered to be low cost, it may be unavailable for many users. In this work, we develop a low-cost system for controlling robots (iRobot) with a web-cam and just red markers on the user’s hands. Our system requires no extra devices, hardware, or other complex technologies. Experimental results of the proposed system demonstrate good results compared to those provided by depth sensors.

Eyeglass replacement system is presented in this work. The proposed system automatically replaces the eyeglass frame from an input frontal face image with another one. First, the system generates a mask that specifies the location of the eyeglass frame in the input image. Next, the unwanted pixels from the image are completed using patch-based synthesis. Finally, the user chooses a new eyeglass frame from a dataset of eyeglass frames to see his/her frontal image with the selected one. One of useful applications of the proposed system is an electronic eyeglasses shop, where the user can replace his/her eyeglass frame with another one from the store and see his/her picture with the new one before buying it. Experimental results show that the proposed system effectively replaces eyeglass frames from the frontal face image of the user.

Eyeglass replacement system is presented in this work. The proposed system automatically replaces the eyeglass frame from an input frontal face image with another one. First, the system generates a mask that specifies the location of the eyeglass frame in the input image. Next, the unwanted pixels from the image are completed using patch-based synthesis. Finally, the user chooses a new eyeglass frame from a dataset of eyeglass frames to see his/her frontal image with the selected one. One of useful applications of the proposed system is an electronic eyeglasses shop, where the user can replace his/her eyeglass frame with another one from the store and see his/her picture with the new one before buying it. Experimental results show that the proposed system effectively replaces eyeglass frames from the frontal face image of the user.