Journal Article10.1049/IET-IPR.2009.0262
Efficient hierarchical matching algorithm for processing uncalibrated stereo vision images and its hardware architecture
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TL;DR: An estimation algorithm, which performs a 2-D correspondence search using a hierarchical search pattern, which can process uncalibrated and non-rectified stereo image pairs, maintaining the computational load within reasonable levels is proposed.
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Abstract: In motion estimation, the sub-pixel matching technique involves the search of sub-sample positions as well as integer-sample positions between the image pairs, choosing the one that gives the best match. Based on this idea, this work proposes an estimation algorithm, which performs a 2-D correspondence search using a hierarchical search pattern. The intermediate results are refined by 3-D cellular automata (CA). The disparity value is then defined using the distance of the matching position. Therefore the proposed algorithm can process uncalibrated and non-rectified stereo image pairs, maintaining the computational load within reasonable levels. Additionally, a hardware architecture of the algorithm is deployed. Its performance has been evaluated on both synthetic and real self-captured image sets. Its attributes, make the proposed method suitable for autonomous outdoor robotic applications.
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Citations
Literature Survey on Stereo Vision Disparity Map Algorithms
TL;DR: This literature survey presents a method of qualitative measurement that is widely used by researchers in the area of stereo vision disparity mappings and notes the implementation of previous software-based and hardware-based algorithms.
Hardware Acceleration of Cellular Automata Physarum polycephalum Model
Nikolaos I. Dourvas,Michail-Antisthenis I. Tsompanas,Georgios Ch. Sirakoulis,Philippos Tsalides +3 more
TL;DR: This study implements a Cellular Automata (CA) model in hardware, which attempts to describe and mimic the behavior of the plasmodium in a maze and presents two FPGA implementations which succeed to take advantage of the CA's inherit parallelism and improve the performance of theCA algorithm when compared with software in terms of computational speed and power consumption.
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Fast Motion Object Detection Algorithm Using Complementary Depth Image on an RGB-D Camera
TL;DR: A new fast motion object-detection algorithm is presented based on the complementary depth images and color information, which is able to detect motion objects without background noise.
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A stereo matching approach based on particle filters and scattered control landmarks
TL;DR: This work reduces the computational redundancy of particle filtering in the authors' stereo correspondence with a Markov chain model, given the previous scan line values, and assists particle filtering convergence by adding a proportional weight in the predicted disparity value estimated by Markov chains.
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Automated Design Architecture for 1-D Cellular Automata Using Quantum Cellular Automata
TL;DR: A new automated design architecture and a tool, namely DATICAQ (Design Automation Tool of 1-D CAs using QCAs), that builds a bridge between 1- d CAs as models of physical systems and processes and 1- D QCAs as nanoelectronic architecture.
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