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Richa R.,Brazilian National Institute for Digital Convergence INCoD | Souza M.,Brazilian National Institute for Digital Convergence INCoD | Scandaroli G.,Brazilian National Institute for Digital Convergence INCoD | Comunello E.,Brazilian National Institute for Digital Convergence INCoD | Von Wangenheim A.,Brazilian National Institute for Digital Convergence INCoD
2014 IEEE International Conference on Image Processing, ICIP 2014 | Year: 2014

Gradient-based optimization is a very efficient strategy to solve the direct visual tracking (DVT) problem using transformation models with many degrees of freedom (DOF). Even though popular DVT methods use the sum of squared differences as similarity function, this approach is not robust to illumination variations often verified in practice. One technique to compensate illumination variations is through an illumination model, which, in turn, increases the total number of parameters to be computed. High quality augmented reality and robotic systems demand fast tracking speeds, which can be impaired by the computational complexity added by the illumination model. In this paper, we propose a robust DVT method capable of tracking in extreme illumination conditions. Building upon the sum of conditional variance as similarity function, we propose a novel tracking method that significantly reduces the computational effort compared to similar methods proposed in the literature. We provide extensive experiments and quantitative analysis using challenging videos to attest the advantages of the proposed method. © 2014 IEEE.


Linhares R.T.,Brazilian National Institute for Digital Convergence INCoD | Richa R.,Brazilian National Institute for Digital Convergence INCoD | Moraes R.,Brazilian National Institute for Digital Convergence INCoD | Comunello E.,Brazilian National Institute for Digital Convergence INCoD | von Wangenheim A.,Brazilian National Institute for Digital Convergence INCoD
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

 Computer assistance has the potential for increasing safety and accuracy during retinal laser treatment using the slit-lamp. In this context, intra-operative retinal mapping is a fundamental requirement to overlay relevant pre-operative information for surgeons. Retinal mapping using the slit-lamp is a challenging task, due to disturbances such as lens distortions, occlusions and glare. Such disturbances have a negative impact on the duration of the mapping procedure, consequently affecting its acceptance in clinical practice. To cope with these visual tracking interruptions, we propose a fast retina map relocalization strategy based on template-matching, using local binary patterns, which are suitable for the retina’s texture. We perform extensive experiments to show the superior accuracy and computational efficiency of the proposed approach in comparison with feature-based methods. © Springer International Publishing Switzerland 2014.


Souza M.,Brazilian National Institute for Digital Convergence INCoD | Richa R.,Brazilian National Institute for Digital Convergence INCoD | Puel A.,Brazilian National Institute for Digital Convergence INCoD | Caetano J.,Brazilian National Institute for Digital Convergence INCoD | And 2 more authors.
Proceedings - IEEE Symposium on Computer-Based Medical Systems | Year: 2014

The slit lamp device is a very popular equipment for inspecting the human retina due to its magnification, stereoscopy and easy control. In this context, computer assistance can provide information overlay to surgeons, improving navigation, accuracy and safety in procedures where the slit-lamp is used. Toward this goal, we describe a robust method for tracking and mapping the human retina using slit-lamp images. Inspired in [1], the proposed method is essentially a direct visual tracking method using local illumination compensation, as well as an efficient pixel selection scheme for achieving fast tracking speeds. In this paper, we describe a novel forward-backward strategy for achieving superior tracking resilience. Experiments conducted on several human patients confirm the practical value of the system. © 2014 IEEE.

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