NDLI: Fuzzy segmentation and recognition of continuous human activities

Content Provider	IEEE Xplore Digital Library
Author	Hao Zhang Wenjun Zhou Parker, L.E.
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, TN, USA (Hao Zhang; Parker, L.E.) \|\| Dept. of Stat., Oper. & Manage. Sci., Univ. of Tennessee, Knoxville, TN, USA (Wenjun Zhou)
Abstract	Most previous research has focused on classifying single human activities contained in segmented videos. However, in real-world scenarios, human activities are inherently continuous and gradual transitions always exist between temporally adjacent activities. In this paper, we propose a Fuzzy Segmentation and Recognition (FuzzySR) algorithm to explicitly model this gradual transition. Our goal is to simultaneously segment a given video into events and recognize the activity contained in each event. Specifically, our algorithm uniformly partitions the video into a sequence of non-overlapping blocks, each of which lasts a short period of time. Then, a multi-variable time series is creatively formed through concatenating the block-level human activity summaries that are computed using topic models over each block's local spatio-temporal features. By representing an event as a fuzzy set that has fuzzy boundaries to model gradual transitions, our algorithm is able to segment the video into a sequence of fuzzy events. By incorporating all block summaries contained in an event, the proposed algorithm determines the most appropriate activity category for each event. We evaluate our algorithm's performance using two real-world benchmark datasets that are widely used in the machine vision community. We also demonstrate our algorithm's effectiveness in important robotics applications, such as intelligent service robotics. For all used datasets, our algorithm achieves promising continuous human activity segmentation and recognition results.
Starting Page	6305
Ending Page	6312
File Size	1195349
Page Count	8
File Format	PDF
ISBN	9781479936854
DOI	10.1109/ICRA.2014.6907789
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Videos Object segmentation Time series analysis Visualization Partitioning algorithms Legged locomotion Hidden Markov models
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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