DocumentCode :
2204570
Title :
Task Prediction in Cooking Activities Using Hierarchical State Space Markov Chain and Object Based Task Grouping
Author :
Lade, Prasanth ; Krishnan, Narayanan C. ; Panchanathan, Sethuraman
Author_Institution :
Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA
fYear :
2010
fDate :
13-15 Dec. 2010
Firstpage :
284
Lastpage :
289
Abstract :
Cooking activities are complex activities consisting of multiple steps or tasks. These tasks can be associated with one another based on two properties the temporal structure that defines the sequence of occurrence of tasks and the objects that are used in the activity. This paper develops cooking activity models for the purpose of task prediction based on these two properties. The temporal structure of the sequence of tasks is captured by the novel hierarchical state space markov chain (HMC) and the object usage is represented using the object based task group (OTG) models. A probabilistic task prediction algorithm that fuses the HMC and OTG models has been developed to predict the next most probable task, given that a sequence of tasks has been completed. The proposed models and algorithms have been evaluated on two complex cooking activities making brownies and making eggs, achieving a subject independent accuracy of 68.5% for predicting tasks, which is an improvement by an average of 6% in comparison to a Markov chain. The work done in the paper is first of its kind as it focuses on task prediction rather than task recognition. The task prediction framework described in the paper can be easily adapted to any complex activity supporting various annotation schemes and activity models.
Keywords :
Markov processes; data structures; home computing; HMC; OTG; cooking activities; hierarchical state space Markov chain; object based task grouping; probabilistic task prediction algorithm; Activity Prediction; Cooking Activties; Hierarchical State Space; Markov Chain; Task Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia (ISM), 2010 IEEE International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-8672-4
Electronic_ISBN :
978-0-7695-4217-1
Type :
conf
DOI :
10.1109/ISM.2010.49
Filename :
5693854
Link To Document :
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