We present a new concept as well as the implementation of an FPGA-based reconfigurable platform, the Erlangen Slot Machine (ESM). The main advantages of this platform are: first, the possibility for each module to access its peripheries independent from its location through a programmable crossbar, and distributed SRAMs among slices. This allows an unrestricted relocation of modules on the device.Second, the intermodule structure allows an unlimited communication among running modules.
Abstract-In this work we propose the application of stateof-the-art feature descriptors into a Particle Filter framework for the lane detection task. The key idea lies on the comparison of image features extracted from the actual measurement with a priori calculated descriptors. First, we demonstrate how a feature expectation can be extracted based on a particle hypothesis. We then propose to define the likelihood function in terms of the distance between the expected feature and the features calculated from the current measurement. We select the Histogram of Oriented Gradients as a descriptor and the Battacharyya distance as a metric. We show that this simple approach is powerful in terms of pattern discrimination and that it opens a new set of possibilities for increasing the robustness of lane detectors.
Abstract. We present a new implementation of the singular value decomposition (SVD) on a reconfigurable system made upon a Pentium processor and a FPGA-board plugged on a PCI slot of the PC. A maximum performance of the SVD is obtained by an efficient distribution of the data and the computation across the FPGA resource. Using the reconfiguration capability of the FPGA help us implement many operators on the same device.
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