TY - GEN
T1 - An introduction to the 3rd workshop on egocentric (first-person) vision
AU - Mann, Steve
AU - Kitani, Kris M.
AU - Lee, Yong Jae
AU - Ryoo, M. S.
AU - Fathi, Alireza
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/24
Y1 - 2014/9/24
N2 - Egocentric vision provides a unique perspective of the visual world that is inherently human-centric. Since egocentric cameras are mounted on the user (typically on the user's head), they are naturally primed to gather visual information from our everyday interactions, and can even act on that information in real-time (e.g. for a vision aid). We believe that this human-centric characteristic of egocentric vision can have a large impact on the way we approach central computer vision tasks such as visual detection, recognition, prediction, and socio-behavioral analysis. By taking advantage of the first-person point-of-view paradigm, there have been recent advances in areas such as personalized video summarization, understanding concepts of social saliency, activity analysis with inside-out cameras (a camera to capture eye gaze and an outward-looking camera), recognizing human interactions and modeling focus of attention. However, in many ways people are only beginning to understand the full potential (and limitations) of the first-person paradigm. In the 3rd workshop on Egocentric (First-Person) Vision, we bring together researchers to discuss emerging topics such as: Personalization of visual analysis; Socio-behavioral modeling; Understanding group dynamics and interactions; Egocentric video as big data; First-person vision for robotics; and Egographical User Interfaces (EUIs).
AB - Egocentric vision provides a unique perspective of the visual world that is inherently human-centric. Since egocentric cameras are mounted on the user (typically on the user's head), they are naturally primed to gather visual information from our everyday interactions, and can even act on that information in real-time (e.g. for a vision aid). We believe that this human-centric characteristic of egocentric vision can have a large impact on the way we approach central computer vision tasks such as visual detection, recognition, prediction, and socio-behavioral analysis. By taking advantage of the first-person point-of-view paradigm, there have been recent advances in areas such as personalized video summarization, understanding concepts of social saliency, activity analysis with inside-out cameras (a camera to capture eye gaze and an outward-looking camera), recognizing human interactions and modeling focus of attention. However, in many ways people are only beginning to understand the full potential (and limitations) of the first-person paradigm. In the 3rd workshop on Egocentric (First-Person) Vision, we bring together researchers to discuss emerging topics such as: Personalization of visual analysis; Socio-behavioral modeling; Understanding group dynamics and interactions; Egocentric video as big data; First-person vision for robotics; and Egographical User Interfaces (EUIs).
UR - https://www.scopus.com/pages/publications/84908538260
U2 - 10.1109/CVPRW.2014.133
DO - 10.1109/CVPRW.2014.133
M3 - Conference contribution
AN - SCOPUS:84908538260
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 827
EP - 832
BT - Proceedings - 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014
PB - IEEE Computer Society
T2 - 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014
Y2 - 23 June 2014 through 28 June 2014
ER -