Using The Concept Hierarchy for Household Action Recognition
We propose a method to systematically represent both the static and the dynamic components of environments, i.e. objects and agents, as well as the changes that are happening in the environment, i.e. the actions and skills performed by agents. Our approach, the Concept Hierarchy, provides the necessary information for autonomous systems to represent environment states, perform action modeling and recognition, and plan the execution of tasks. Additionally, the hierarchical structure supports generalization and knowledge transfer to environments. We rigorously define tasks, actions, skills, and affordances that enable human-understandable action and skill recognition.
Code (0)
등록된 구현이 없습니다.
Tasks
Action RecognitionTransfer LearningSimilar Papers 제목 키워드 기반
Learning multimodal representations for sample-efficient recognition of human actions
Humans interact in rich and diverse ways with the environment. However, the representation of such behavior by artificial agents is often limited. In this work we present \textit{motion concepts}, a novel multimodal repr…
Faceted Hierarchy: A New Graph Type to Organize Scientific Concepts and a Construction Method
On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as a…
Face RecognitionHyponymy extraction of domain ontology concept based on ccrfs and hierarchy clustering
Concept hierarchy is the backbone of ontology, and the concept hierarchy acquisition has been a hot topic in the field of ontology learning. this paper proposes a hyponymy extraction method of domain ontology concept bas…
ClusteringExamining Interpretable Feature Relationships in Deep Networks for Action recognition
A number of recent methods to understand neural networks have focused on quantifying the role of individual features. One such method, NetDissect identifies interpretable features of a model using the Broden dataset of …
Action RecognitionOnline Hierarchical Forecasting for Power Consumption Data
We study the forecasting of the power consumptions of a population of households and of subpopulations thereof. These subpopulations are built according to location, to exogenous information and/or to profiles we determi…
Additive modelsTime SeriesTime Series Analysis