A fine-grained perspective onto object interactions from first-person views

8 February 2019, 4.00 PM - 8 February 2019, 5.00 PM

Dima Damen, Associate Professor, University of Bristol

Life Sciences Building, G13/14

Abstract 

Traditionally, action understanding has been limited to assigning one out of a pre-selected set of labels to a trimmed video sequence. This talk goes beyond traditional action recognition to a fine-grained understanding of daily object interactions. Dima will discuss works that attempt to understand ‘when’ an object interaction takes place, including ‘when’ it can be considered completed, ‘which’ semantic labels can describe the interactions, ‘how’ the interaction can be described (or captioned) and ‘who’ is better when contrasting people perform the same interaction. Potentials and limitations of current deep architectures to solve for fine-grained object interaction understanding will be discussed.

It will also focus on the first-person viewpoint – captured using wearable cameras- as it offers a unique perspective onto objects during interactions.

Brief Biography

Dima Damen is Associate Professor in Computer Vision at the University of Bristol and received her PhD from the University of Leeds, UK (2009). Dima's research interests are in the automatic understanding of object interactions, actions and activities using wearable and static visual (and depth) sensors. She has contributed works to novel research questions including fine-grained object interaction recognition, understanding the completion of actions, skill determination from video, semantic ambiguities of actions and the robustness of classifiers to action’s temporal boundaries. 

Her work is published in leading venues: CVPR, ECCV, ICCV, PAMI, IJCV, CVIU and BMVC. In 2018, she led on releasing the largest dataset in first-person vision to date (EPIC-KITCHENS) - 11.5M frames of non-scripted recordings with full ground truth. Dima co-chaired BMVC 2013, is area chair for BMVC (2014-2018), associate editor of Pattern Recognition (2017-). She was selected as a Nokia Research collaborator in 2016, and as an Outstanding Reviewer in ICCV17, CVPR13 and CVPR12. 

http://people.cs.bris.ac.uk/~damen//

 

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