Michael Maynord

Michael Maynord
University of Maryland, College Park | UMD, UMCP, University of Maryland College Park · Department of Computer Science

About

9
Publications
811
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30
Citations
Citations since 2016
7 Research Items
29 Citations
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Publications

Publications (9)
Chapter
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Action plays a central role in our lives and environments, yet most Computer Vision methods do not explicitly model action. In this chapter we outline an action-centric framework which spans multiple time scales and levels of abstraction, producing both action and scene interpretations constrained towards action consistency. At the lower level of t...
Preprint
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Human actions involving hand manipulations are structured according to the making and breaking of hand-object contact, and human visual understanding of action is reliant on anticipation of contact as is demonstrated by pioneering work in cognitive science. Taking inspiration from this, we introduce representations and models centered on contact, w...
Article
Human visual understanding of action is reliant on anticipation of contact as is demonstrated by pioneering work in cognitive science. Taking inspiration from this, we introduce representations and models centered on contact, which we then use in action prediction and anticipation. We annotate a subset of the EPIC Kitchens dataset to include time-t...
Preprint
Full-text available
We introduce Egocentric Object Manipulation Graphs (Ego-OMG) - a novel representation for activity modeling and anticipation of near future actions integrating three components: 1) semantic temporal structure of activities, 2) short-term dynamics, and 3) representations for appearance. Semantic temporal structure is modeled through a graph, embedde...
Preprint
Full-text available
In this paper we demonstrate that state-of-the-art convolutional neural networks can be constructed using a cascade algorithm for deep networks, inspired by the cascade algorithm in wavelet analysis. For each network layer the cascade algorithm creates two streams of features from the previous layer: one stream modulates the existing features produ...
Article
We describe our Meta-cognitive, Integrated, Dual-Cycle Architecture (MIDCA), whose purpose is to provide agents with a greater capacity for acting in an open world and dealing with unexpected events. We present MIDCA-1.0, a partial implementation which explores a novel machine-learning approach to goal generation using the Tilde and FOIL algorithms...
Article
We describe an iPad app which assists in language acquisition and development. Such an application can be used by clinicians for human developmental disabilities. A user drags images around on the screen. The app generates and speaks random (but sensible) phrases that matches the image interact. For example, if a user drags an image of a squirrel o...

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