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Parallel random sampling consensus method and device

A consistent sampling and random sampling technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as speed bottlenecks, dependence on power consumption, and application limitations, and achieve improved robustness and data throughput The effect of volume and low power consumption

Active Publication Date: 2013-09-18
BEIHANG UNIV
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Problems solved by technology

These parallelization methods simply divide the serial scheme into multiple threads to execute simultaneously, and serial operations are still required to find the best model. Although the acceleration effect is achieved, there are still speed bottlenecks in some places, which depend on the computer platform and High power consumption, limited applications

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  • Parallel random sampling consensus method and device

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Embodiment 1

[0090] Let the time complexity of the traditional RANSAC method be ο(n 2 ). When the amount of data is large, the proportion of outliers is high, and the model is complex, k and N (the size of dataset A) increase rapidly, and the performance of the algorithm is seriously affected. In existing parallel algorithms, the time complexity is reduced to ο(n). Here, k is the minimum number of iterations that can guarantee a certain success probability of traditional serial RANSAC, where

[0091] Since the parallel RANSAC method of the present invention does not need to verify the optimal model again, the speed is increased to twice that of the existing parallel methods based on GPUs and the like, and the performance improvement can also be realized on other parallel computing platforms. Table 2 shows the performance comparison of three RANSAC methods in the serial mode, the parallel mode in the prior art, and the parallel mode in the present invention, where k>1.

[0092]

[0...

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Abstract

The invention discloses a parallel random sampling consensus (RANSAC) method. An assuming stage and a verification stage in the parallel RANSAC method are performed parallelly. Specifically, the method comprises the steps of parallelly acquiring m groups of random samples ai(i=1,2,...,m) from a data set A with N data numbers in the assuming stage and parallelly outputting m estimated models Mi(i=1,2,...,m) according to the m groups of random samples ai(i=1,2,...,m); adopting the m estimated models Mi(i=1,2,...,m) to parallelly vote the same point in the verification stage and gradually and directly judging whether each point in the data set A is an inside point or not. The invention further discloses a parallel RANSAC device. By adopting the parallel RANSAC method and the parallel RANSAC device, the performance and data throughout amount of an RANSAC algorithm can be improved, and the demand for high-speed real-time processing can be met.

Description

technical field [0001] The present invention relates to a model parameter estimation method, in particular to a parallel random sampling consensus (RANSAC, RANdom SAmple Consensus) method and device thereof. Background technique [0002] The RANSAC method is a model parameter estimation method with good robustness. Due to its simple hypothesis-testing principle and strong robustness, the RANSAC method has been widely used in model estimation with erroneous data, such as target detection and stereo image matching. Wait. [0003] The traditional RANSAC method is implemented in a serial manner. The basic principles of the specific implementation are: [0004] (1) When the size is N, the number of intra-office points is N inliers A set of samples a consisting of n (n is the minimum number of points required to estimate the model) are randomly sampled from the dataset A of i , and use it to estimate a model M i ; [0005] (2) Check all the data in A, if it conforms to M i e...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 江洁凌思睿
Owner BEIHANG UNIV
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