Title

University Of Central Florida At Trecvid 2008 Content Based Copy Detection And Surveillance Event Detection

Abstract

In this paper, we describe our approaches and experiments in content-based copy detection (CBCD) and surveillance event detection pilot (SEDP) tasks of TRECVID 2008. We have participated in the video-only CBCD task and four of the SEDP events. The CBCD method relies on sequences of invariant global image features and efficiently matching and ranking of those sequences. The normalized Hu-moments are proven to be invariant to many transformations, as well as certain level of noise, and thus are the basis of our system. The most crucial property of proposed CBCD system is that it relies on the sequence matching rather than independent frame correspondences. The experiments have shown that this approach is quite useful for matching videos under extensive and strong transformations which make single frame matching a challenging task. This methodology is proven to be fast and produce high F1 detection scores in the TRECVID 2008 task evaluation. We also submitted four individual surveillance event detection systems. "Person-Runs", "Object-Put", "Opposing-Flow" and "Take-Picture" are the four selected events. The systems rely on low level vision properties such as optical flow and image intensity as well as heuristics based on a given event and context.

Publication Date

1-1-2008

Publication Title

2008 TREC Video Retrieval Evaluation Notebook Papers

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84905181684 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84905181684

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