The idea of managing the comprising computations of an application executed in an FPGA-based system is presented. An efficient algorithm for exploiting the timing slack of building blocks of the application is proposed. The slack of these blocks can be utilized by replacing them with slower but "cheaper" modules and by assigning the computations to the proper resources. Thus, our approach manages the comprising computations and system resources at the same time. This is performed without compromising the timing constraints of the application and can lead to significant improvements in power dissipation, computation accuracy or other design metrics based on the application domain. Our algorithm is well-suited for arbitrary tree computations. Moreover, it delivers solutions that are desirably close to the optimal solution. Experimental results for a number of object tracking applications executed on resources embedded in cameras, show a significant amount of slack utilization.

In this paper, we describe experiments conducted to explain observed differences in the bright pupil response of human eyes. Many people observe the bright pupil response as the red-eye effect when taking flash photography. However, there is significant variation in the magnitude of the bright pupil response across the population. Since many commercial gaze-tracking systems use the infrared bright pupil response for eye detection, a clear understanding of the magnitude and cause of the bright pupil variation gives critical insight into the robustness of gaze tracking systems. This paper documents studies we have conducted to measure the bright pupil differences using infrared light and hypothesis factors that lead to these differences.