Learning informative features for spatial histogram-based object detection free
Request PDF on ResearchGate Learning informative features for spatial histogrambased object detection Feature extraction for object representation plays an important role in automatic object
exible for object detection still remains an open problem. Motivated by the observation that objects have texture distribution and shape conguration, we propose spatial histogram based features (termed as spatial histogram features) to represent objects. As spatial histograms consist of marginal distributions of an image over local patches,
As the spatial histograms consist of marginal distribution of image over local patches, object texture and shape are simultaneously preserved by the spatial histogram representation. In this paper, we propose methods of learning informative features for spatial histogrambased object detection.
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, they can preserve
Improved face detection using spatial histogram features Hamid Parvin 1, Hosein Alizadeh, Mahmood Fathi and Behrouz MinaeiBidgoli 1Department of Computer Engineering, Iran University of Science
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