Rostam Affendi Hamzah
Papers
5
Total Citations
65
H-Index
5
About
Rostam Affendi Hamzah is a robotics and computer vision researcher whose work has centered on advancing stereo vision systems for autonomous mobile robot navigation. His most significant contributions lie in solving the stereo correspondence problem — a fundamental challenge in extracting meaningful 3D spatial information from paired camera images. Through his pioneering application of block matching algorithms utilizing Sum of Absolute Differences (SAD), Hamzah developed practical frameworks for disparity mapping and depth evaluation that enable robots to perceive and navigate real-world environments with greater accuracy. His most-cited work, published in 2010 with 20 citations, established foundational techniques for stereo image comparison that directly informed subsequent research on obstacle detection and avoidance systems. Building on this, his 2011 paper demonstrated real-world indoor navigation capabilities, accumulating 17 citations and showcasing the practical viability of his approaches. Hamzah has also made notable contributions to camera calibration methodology, employing both Tsai's method and Bouguet's toolbox to correct image distortion and improve stereo rectification accuracy. Collectively, his body of work — spanning disparity analysis, depth perception, and calibration techniques — has provided researchers and engineers with accessible, implementable solutions that continue to influence stereo vision robotics development.
Research Focus
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Top Papers
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