Journal ArticleDOI
Dynamic sensor data segmentation for real-time knowledge-driven activity recognition
TLDR
A novel approach to real-time sensor data segmentation for continuous activity recognition based on the notion of varied time windows, which can shrink and expand the segmentation window size by using temporal information of sensor data and activities as well as the state of activity recognition.About:
This article is published in Pervasive and Mobile Computing.The article was published on 2014-02-01. It has received 159 citations till now. The article focuses on the topics: Activity recognition & Segmentation.read more
Citations
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Journal ArticleDOI
Computer vision for assistive technologies
TL;DR: An original "task oriented" way to categorize the state of the art of the AT works has been introduced that relies on the split of the final assistive goals into tasks that are then used as pointers to the works in literature in which each of them has been used as a component.
Journal ArticleDOI
An Ontology-Based Hybrid Approach to Activity Modeling for Smart Homes
TL;DR: An ontology-based hybrid approach to activity modeling that combines domain knowledge based model specification and data-driven model learning is introduced that has been implemented in a feature-rich assistive living system.
Journal ArticleDOI
Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review.
TL;DR: The state-of-the-art in traditional PARM methodologies as used in the healthcare domain, including sensory, feature extraction and recognition techniques are summarized, and some key enabling techniques for tackling them are discussed.
Journal ArticleDOI
Dynamic sensor event segmentation for real-time activity recognition in a smart home context
TL;DR: A novel near real-time sensor segmentation approach that incorporates the notions of both sensor and time correlation is presented.
Journal ArticleDOI
KCAR: A knowledge-driven approach for concurrent activity recognition
TL;DR: This paper presents a novel Knowledge-driven approach for Concurrent Activity Recognition (KCAR), which exploits the Pyramid Match Kernel, with a strength in approximate matching on hierarchical concepts, to recognise activities of varying grained constraints from a potentially noisy sensor sequence.
References
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Journal ArticleDOI
A translation approach to portable ontology specifications
TL;DR: This paper describes a mechanism for defining ontologies that are portable over representation systems, basing Ontolingua itself on an ontology of domain-independent, representational idioms.
Book ChapterDOI
Activity recognition from user-annotated acceleration data
Ling Bao,Stephen S. Intille +1 more
TL;DR: This is the first work to investigate performance of recognition algorithms with multiple, wire-free accelerometers on 20 activities using datasets annotated by the subjects themselves, and suggests that multiple accelerometers aid in recognition.
Journal ArticleDOI
Machine Recognition of Human Activities: A Survey
TL;DR: A comprehensive survey of efforts in the past couple of decades to address the problems of representation, recognition, and learning of human activities from video and related applications is presented.
Book ChapterDOI
Activity Recognition in the Home Using Simple and Ubiquitous Sensors
TL;DR: Preliminary results on a small dataset show that it is possible to recognize activities of interest to medical professionals such as toileting, bathing, and grooming with detection accuracies ranging from 25% to 89% depending on the evaluation criteria used.
Journal ArticleDOI
Inferring activities from interactions with objects
Matthai Philipose,Kenneth P. Fishkin,Mike Perkowitz,Donald J. Patterson,Dieter Fox,Henry Kautz,Dirk Hähnel +6 more
TL;DR: The key observation is that the sequence of objects a person uses while performing an ADL robustly characterizes both the ADL's identity and the quality of its execution.