Detecting social interaction in videos relying solely on visual cues is a valuable task that is receiving increasing attention in recent years. In this work, we address this problem in the challenging domain of egocentric photo-streams captured by a low temporal resolution wearable camera (2fpm). The major difficulties to be handled in this context are the sparsity of observations as well as unpredictability of camera motion and attention orientation due to the fact that the camera is worn as part of clothing. Our method consists of four steps: multi-faces localization and tracking, 3D localization, pose estimation and analysis of f-formations. By estimating pair-to-pair interaction probabilities over the sequence, our method states the presence or absence of interaction with the camera wearer and specifies which people are more involved in the interaction. We tested our method over a dataset of 18.000 images and we show its reliability on our considered purpose.
This paper deals with the joint use of connected operators and image inpainting for image filtering. Connected
operators filter the image by merging its flat zones while preserving contour information. Image inpainting
restores the values of an image for a destroyed or consciously masked subregion of the image domain. In the
present paper, it will be shown that image inpainting can be combined with connected operators to perform
an efficient geometrical filtering technique. First, connected operators are presented and their drawbacks for
certain applications are highlighted. Second, image inpainting methodology is introduced and a structural image
inpainting algorithm is described. Finally, a general filtering scheme is proposed to show how the drawbacks of
connected operators can be efficiently solved by structural image inpainting.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.