Dr. Zhoudi Huang Profile

Dr. Zhoudi Huang

at Beihang University

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Publications (2)

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Proceedings Article | 12 December 2018 Paper

An outdoor accuracy evaluation method of aircraft flight attitude dynamic vison measure system

Binhu Chai, Fulin Liu, Zhoudi Huang, Ke Tan, Zhenzhong Wei

Proceedings Volume 10846, 1084635 (2018) https://doi.org/10.1117/12.2505671

KEYWORDS: Photography, 3D imaging standards, 3D metrology, Dynamical systems, 3D acquisition, Standards development, Visualization, Commercial off the shelf technology, Image quality, Opto mechatronics

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The aircraft flight attitude can be obtained by the dynamic visual measurement system for aircraft (hereinafter short for MSA). It is crucial for MSA to evaluate its flight attitude measurement accuracy. There are several indoor evaluation methods for the MSA’s attitude measurement accuracy which is not suitable outdoors. Therefore, we present a method for evaluating its flight attitude measurement accuracy at outdoor working site. A three-dimensional standard verification field can be established by reasonable distribution of mark targets on the surface of outdoor building group. We construct a verification system for flight attitude measurement accuracy at outdoor working site. The building group whose threedimension scale is similar to the aircraft’s three-dimension scale is selected to construct the standard verification field. Paste mark points on the surface of the building group and their coordinates in 3D space are measured by the threedimensional coordinate measuring station consisting of two electronic theodolites. Mark points with known coordinates construct the standard verification field. Still photographs of the standard verification field are taken by the MSA. the attitude solved from the still photographs is used as reference attitude. Manipulate the MSA to shoot and record dynamically to simulate the real working condition, and photographs are taken to solve the dynamic measurement attitude at the same time. Accuracy analysis and evaluation can be performed using the dynamic measurement attitude and the reference attitude to provide scientific basis for debugging, checking outdoor parameters and acceptance of equipment.

Proceedings Article | 1 November 2016 Paper

Learning to assign binary weights to binary descriptor

Zhoudi Huang, Zhenzhong Wei, Guangjun Zhang

Proceedings Volume 10157, 1015721 (2016) https://doi.org/10.1117/12.2246737

KEYWORDS: Binary data

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Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

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