| Design of a digital library for human movement |
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International Conference on Digital Libraries
archive
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
table of contents
Roanoke, Virginia, United States
Pages: 300 - 309
Year of Publication: 2001
ISBN:1-58113-345-6
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Authors
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Jezekiel Ben-Arie
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EECS Department M/C 154m, University of Illinois at Chicago, 851 S. Morgan St., SEO 1120, Chicago, IL
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Purvin Pandit
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EECS Department, University of Illinois at Chicago
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ShyamSundar Rajaram
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EECS Department, University of Illinois at Chicago
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| Bibliometrics |
Downloads (6 Weeks): 3, Downloads (12 Months): 37, Citation Count: 2
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ABSTRACT
This paper is focused on a central aspect in the design of our planned digital library for human movement, i.e. on the aspect of representation and recognition of human activity from video data. The method of representation is important since it has a major impact on the design of all the other building blocks of our system such as the user interface/query block or the activity recognition/storage block. In this paper we evaluate a representation method for human movement that is based on sequences of angular poses and angular velocities of the human skeletal joints, for storage and retrieval of human actions in video databases. The choice of a representation method plays an important role in the database structure, search methods, storage efficiency etc.. For this representation, we develop a novel approach for complex human activity recognition by employing multidimensional indexing combined with temporal or sequential correlation. This scheme is then evaluated with respect to its efficiency in storage and retrieval.For the indexing we use postures of humans in videos that are decomposed into a set of multidimensional tuples which represent the poses/velocities of human body parts such as arms, legs and torso. Three novel methods for human activity recognition are theoretically and experimentally compared. The methods require only a few sparsely sampled human postures. We also achieve speed invariant recognition of activities by eliminating the time factor and replacing it with sequence information. The indexing approach also provides robust recognition and an efficient storage/retrieval of all the activities in a small set of hash tables.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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INDEX TERMS
Primary Classification:
I.
Computing Methodologies
I.4
IMAGE PROCESSING AND COMPUTER VISION
Additional Classification:
E.
Data
H.
Information Systems
H.3
INFORMATION STORAGE AND RETRIEVAL
H.3.1
Content Analysis and Indexing
Subjects:
Indexing methods
I.
Computing Methodologies
I.4
IMAGE PROCESSING AND COMPUTER VISION
I.4.8
Scene Analysis
Subjects:
Motion;
Tracking
I.5
PATTERN RECOGNITION
I.5.2
Design Methodology
Subjects:
Pattern analysis
General Terms:
Algorithms,
Design,
Documentation,
Experimentation,
Human Factors,
Management,
Measurement,
Performance,
Theory
Keywords:
human activity recognition,
multi dimenional indexing,
sequence recognition,
temporal correlation
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