Activity recognition via classification constrained diffusion maps

Yunqian Ma, S. B. Damelin, O. Masoud, N. Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


Applying advanced video technology to understand human activity and intent is becoming increasingly important for video surveillance. In this paper, we perform automatic activity recognition by classification of spatial temporal features from video sequence. We propose to incorporate class labels information to find optimal heating time for dimensionality reduction using diffusion via random walks. We perform experiments on real data, and compare the proposed method with existing random walk diffusion map method and dual root minimal spanning tree diffusion method. Experimental results show that our proposed method is better.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - Second International Symposium, ISVC 2006, Proceedings
PublisherSpringer Verlag
Number of pages8
ISBN (Print)3540486283, 9783540486282
StatePublished - 2006
Event2nd International Symposium on Visual Computing, ISVC 2006 - Lake Tahoe, NV, United States
Duration: Nov 6 2006Nov 8 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4291 LNCS - I
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2nd International Symposium on Visual Computing, ISVC 2006
Country/TerritoryUnited States
CityLake Tahoe, NV


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