Object specific deep feature and its application to face detection

Xianxu Hou, Jiasong Zhu, Ke Sun, Linlin Shen, Guoping Qiu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

We present a method for exploiting object specific deep features and use face detection as a case study. We seek to discover and exploit the convolutional channels of a CNN in which neurons are activated by the presence of specific objects in the input image. A method for explicitly fine-tuning a pre-trained CNN to induce an object specific channel (OSC) and systematically identifying it for the human face object has been developed. Building on the basic OSC features, we introduce a multi-scale approach to constructing robust face heatmaps for rapidly filtering out non-face regions thus significantly improving search efficiency for face detection in unconstrained settings. We show that multi-scale OSC can be used to develop simple and compact face detectors with state of the art performance.

Original languageEnglish
Title of host publicationProceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages173-176
Number of pages4
ISBN (Electronic)9784901122160
DOIs
Publication statusPublished - 19 Jul 2017
Externally publishedYes
Event15th IAPR International Conference on Machine Vision Applications, MVA 2017 - Nagoya, Japan
Duration: 8 May 201712 May 2017

Publication series

NameProceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017

Conference

Conference15th IAPR International Conference on Machine Vision Applications, MVA 2017
Country/TerritoryJapan
CityNagoya
Period8/05/1712/05/17

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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