An applied study of human detection in single images

Ren Liu; Xianghua Xie

doi:10.1117/12.917683

15 November 2011 An applied study of human detection in single images

Ren Liu, Xianghua Xie

Proceedings Volume 8335, 2012 International Workshop on Image Processing and Optical Engineering; 83350D (2011) https://doi.org/10.1117/12.917683
Event: 2012 International Workshop on Image Processing and Optical Engineering, 2012, Harbin, China

Abstract

In this paper we perform an applied comparative study of popular HOG based human detection and a state-of-the-art pose adaptive method that uses shape-based model construction. Both methods are implemented with kernel SVM, instead of linear SVM. Detailed performance evaluation is carried out on MIT pedestrian dataset and INRIA person dataset. This study shows that, although pose adaptive method has no significant advantage compared to the HOG based approach on those datasets, the pose adaptive approach is more efficient in detection and it has the capability to segment the human shape from images while carrying out detection which can be advantageous in many applications.

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Ren Liu and Xianghua Xie "An applied study of human detection in single images", Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83350D (15 November 2011); https://doi.org/10.1117/12.917683

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KEYWORDS

Image segmentation

Sensors

Feature extraction

Binary data

Head

Motion models

Error analysis

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