Large Crowd Count Based on Improved SURF Algorithm
Abstract: This paper uses an
analysis of Speeded up Robust Feature (SURF), based on the method of Linear
Interpolation for camera distortion calibration, for high-density crowd counting.
The eigenvalues are built on the Gray Level Co-occurrence Matrix (GLCM)
features and the SURF features. Though the method of linear interpolation,
weight values are interpolated to reduce the error, which is caused by camera
distortion calibration. The optimized crowd’s feature vector can be got then.
Through the method of support vector regression, the crowd’s number can be
forecast by training model. The experiment result shows that the method of this
paper has a higher accuracy than the previous methods.
Author: Haining Zhang, Huanbo
Gao
Journal Code: jptkomputergg140101
