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We proposed a visual saliency detection model for color images based on the reconstruction residual of quaternion sparse model in this paper. This algorithm measures saliency of color image region by the reconstruction residual and performs more consistent with visual perception than current sparse models. In current sparse models, they treat the color images as multiple independent channel images...
To destroy a country's physical electric power infrastructure by attacking its control system through cyber means, has become an important way to weaken a country's war power. Along with the construction of next generation smart grid, development of the internet of things and appearance of system of systems(henceforth, SOS) warfare based on information systems, the complicated control networks system...
Pervasive computing systems are begging for programming models and methodologies specifically suited to the particular cyber-physical nature of these systems. Reactive (rule-based) programming is an attractive model to use due to its built-in safety features and intuitive application development style. Without careful optimization however, reactive programming engines could turn into monstrous power...
Modeling moving and deforming objects requires capturing as much information as possible during a very short time. When using off-the-shelf hardware, this often hinders the resolution and accuracy of the acquired model. Our key observation is that in as little as four frames both sparse surface-positional measurements and dense surface-orientation measurements can be acquired using a combination of...
Robust foreground detection is a fundamental precursor of many video processing applications. Although various approaches were advanced, there still exist many factors making detection very challenging: 1) Dynamic background with gradual brightness changes, camera movement and large amount of noises. 2) Sharp illumination changes caused by shadows, light on-off, and so on. 3) Real-time requirement...
This article presents a global optimization approach to reconstruct surfaces from a single document image. Instead of assuming globally developable in previous works which restricted the surface to be cylindrical, conical, etc, we use a free form parametric model which is simple yet expressive enough in the reconstruction task. We then apply developable constraints locally on sample points from extracted...
Standard hidden Markov model (HMM) and the more general dynamic Bayesian network (DBN) models assume stationarity of state transition distribution. However, this assumption does not hold for many real life events of interest. In this paper, we propose a new time sequence model that extends HMM to time varying scenario. The time varying property is realized in our model by explicitly allowing the change...
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