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Tiny Head Pose Classification by Bodily Cues

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Citation Author(s):
Irtiza Hasan, Theodore Tsesmelis, Fabio Galasso , Alessio Del Bue, Marco Cristani
Submitted by:
Irtiza Hasan
Last updated:
14 September 2017 - 5:40am
Document Type:
Poster
Document Year:
2017
Event:
Presenters Name:
Irtiza Hasan
Paper Code:
3533

Abstract 

Abstract: 

The head pose is an important cue for computer vision. Traditionally considered in human computer interaction applications,
it becomes very hard to model in surveillance scenarios, due to the tiny head size. Additionally, no public dataset contains continuous head pose annotations in open scenery, making the challenge even harder to face. Here we present a
framework based on Faster RCNN, which introduces a branch in the network architecture related to the head pose estimation.
The key idea is to leverage the presence of the people body to better infer the head pose, through a joint optimization
process. Additionally, we enrich the Town Center dataset with head pose labels, promoting further study on this topic.
Results on this novel benchmark and ablation studies on other task-specific datasets promote our idea and confirm the importance of the body cues to contextualize the head pose estimation.

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ICIP1701

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