In:
Advances in Mechanical Engineering, SAGE Publications, Vol. 9, No. 1 ( 2017-01), p. 168781401668359-
Abstract:
We present a novel pedestrian count estimation approach based on global image descriptors formed from multi-scale texture features that considers spatial distribution. For regions of interest, local texture features are represented based on histograms of multi-scale block local binary pattern, which jointly constitute the feature vector of the whole image. Therefore, to achieve an effective estimation of pedestrian count, principal component analysis is used to reduce the dimension of the global representation features, and a fitting model between image global features and pedestrian count is constructed via support vector regression. The experimental result shows that the proposed method exhibits high accuracy on pedestrian count estimation and can be applied well in the real world.
Type of Medium:
Online Resource
ISSN:
1687-8140
,
1687-8140
DOI:
10.1177/1687814016683599
Language:
English
Publisher:
SAGE Publications
Publication Date:
2017
detail.hit.zdb_id:
2501620-9
