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Face recognition in real scenarios is mainly affected by illumination variation and occlusion, and therefore in order to develop a robust face recognition system these issues should be handled simultaneously. To this aim, the steps involved in the presented framework are (i) computationally simple and efficient preprocessing chain that eliminates major effects of illumination variation and noise while...
Mutual Information (MI) is one of the main methods for efficient registration of multiband images in the literature. Since images on different bands are often expressed in different numbers of bits, contrast enhancement is inevitable before MI-based image registration. Although the contrast enhancement method used has a significant effect on the registration performance due to MI metric, this problem...
Performing high accurate pose estimation has been an attractive research area in the field of computer vision; hence, there are a plenty of algorithms proposed for this purpose. Starting with RGB or gray scale image data, methods utilizing data from 3D sensors, such as Time of Flight (TOF) or laser range finder, and later those based on RGBD data have emerged chronologically. Algorithms that exploit...
In robotics and augmented reality applications, model-based 3-D tracking of rigid objects is generally required. With the help of accurate pose estimates, it is required to increase reliability and decrease jitter in total. Among many solutions of pose estimation in the literature, pure vision-based 3-D trackers require either manual initializations or offline training stages. On the other hand, trackers...
3D tracking of rigid objects is required in many applications, such as robotics or augmented reality (AR). The availability of accurate pose estimates increases reliability in robotic applications and decreases jitter in AR scenarios. Pure vision-based 3D trackers require either manual initializations or offline training stages, whereas trackers relying on pure depth sensors are not suitable for AR...
Applications such as robotics and augmented reality (AR) require 3D tracking of rigid objects. In robotic applications, the availability of accurate and robust pose estimates increases reliability, whereas in AR scenarios reliable pose estimates decrease jitter. Pure vision sensor based 3D trackers require either manual initializations of pose or off-line training stages. On the other hand, trackers...
The three dimensional (3D) tracking of rigid objects is required in many applications such as 3D television (3DTV) and augmented reality. The availability of consecutive camera positions enables 3D scene reconstruction in 3DTV applications. On the other hand, in augmented reality applications, the knowledge of the pose between camera and scene (or object) reference frames enables the addition of virtual...
A 3D geometry-based multi-view video coding (MVC) method is proposed. In order to utilize the spatial redundancies between multiple views, the scene geometry is estimated as dense depth maps. The dense depth estimation problem is modeled by using a Markov random field (MRF) and solved via the belief propagation algorithm. Relying on these depth maps of the scene, novel view estimates of the intermediate...
A geometry-based multi-view video coding (MVC) method is proposed. In order to utilize the spatial redundancies between multiple views, the scene geometry is estimated as dense depth maps. The dense depth estimation problem is modeled by using a Markov random field (MRF) and solved via the belief propagation algorithm. Relying on these depth maps of the scene, novel view estimates of the intermediate...
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