Paper Info
Title
Video-based activity analysis using the L1 tracker on VIRAT data
Abstract
Developments in video tracking have addressed various aspects such as target detection, tracking accuracy, algorithm comparison, and implementation methods which are briefly reviewed. However, there are other attributes of full motion video (FMV) tracking that require further investigation for situation awareness of event and activity analysis. Key aspects of activity and behavior analysis include interaction between individuals, groups, and crowds as well as with objects in the environment like vehicles and buildings over a specified time duration as it is typically assumed that the activities of interest include people. In this paper, we explore activity analysis using the L1 tracker over various scenarios in the VIRAT data. Activity analysis extends event detection from tracking accuracy to characterizing number, types, and relationships between actors in analyzing human activities of interest. Relationships include correlation in space and time of actors with other people, objects, vehicles, and facilities (POVF). Event detection is more mature (e.g., based on image exploitation and tracking techniques), while activity analysis (as a higher level fusion function) requires innovative techniques for relationship understanding.
Year
DOI
Venue
2013
10.1109/AIPR.2013.6749311
Applied Imagery Pattern Recognition Workshop: Sensing for Control and Augmentation, 2013 IEEE
Keywords
Field
DocType
object detection,FMV tracking,L1 tracker,POVF,VlRAT data,activity analysis,actor relationships,actor space,actor time,algorithm comparison,behavior analysis,buildings,crowd interaction,environment like vehicles,event detection,event situation awareness,full motion video,group interaction,higher level fusion function,human activities,image exploitation,implementation methods,individual interaction,innovative techniques,key activity aspects,number characterization,people object vehicle and facilities,specified time duration,target detection,tracking accuracy,tracking techniques,type characterization,video tracking developments,video-based activity analysis,Activity Analyiss,Exploitation,Full-Motion Video,L1 tracking,Measures of Effectiveness
Object detection,Computer vision,Crowds,Full motion video,Situation awareness,Computer science,Video tracking,Correlation,Artificial intelligence
Conference
ISSN
Citations 
PageRank 
1550-5219
9
0.68
References 
Authors
43
8
Name
Order
Citations
PageRank
Erik Blasch1105190.91
Zhonghai Wang2576.04
Haibin Ling34531215.76
Kannappan Palaniappan492075.13
Genshe Chen544541.82
Dan Shen6222.02
Alex Aved7151.81
Guna Seetharaman858444.59