TAILIEUCHUNG - Event Detection from Flickr Data through Wavelet-based Spatial Analysis

For this paper, we have examined the concept of an investigation to determine what is required. The result is an event-based framework that can be used to develop hypotheses and answer questions about an incident or crime. Hypotheses are developed by collecting objects that may have played a role in an event that was related to the incident. Once the objects are collected as evidence, the investigator can develop hypotheses about previous events at the crime scene. This framework is based on the process model that is used at physical crime scenes, which has been refined from being used for dozens of years and accepted in. | Event Detection from Flickr Data through Wavelet-based Spatial Analysis Ling Chen L3S Research Center Leibniz University Hannover lchen@ Abhishek Roy Indian Institute of Technology Guwahati India ABSTRACT Detecting events from web resources has attracted increasing research interests in recent years. Our focus in this paper is to detect events from photos on Flickr an Internet image community website. The results can be used to facilitate user searching and browsing photos by events. The problem is challenging considering 1 Flickr data is noisy because there are photos unrelated to real-world events 2 It is not easy to capture the content of photos. This paper presents our effort in detecting events from Flickr photos by exploiting the tags supplied by users to annotate photos. In particular the temporal and locational distributions of tag usage are analyzed in the first place where a wavelet transform is employed to suppress noise. Then we identify tags related with events and further distinguish between tags of aperiodic events and those of periodic events. Afterwards event-related tags are clustered such that each cluster representing an event consists of tags with similar temporal and locational distribution patterns as well as with similar associated photos. Finally for each tag cluster photos corresponding to the represented event are extracted. We evaluate the performance of our approach using a set of real data collected from Flickr. The experimental results demonstrate that our approach is effective in detecting events from the Flickr photo collection. Categories and Subject Descriptors H. Information Systems Information Storage and Retrieval Information Search and retrieval General Terms Algorithms Experimentation Measurement Keywords event detection flickr tag wavelet transform I. INTRODUCTION Due to the rapid advancement of digital technology in the last two decades there has been an increasingly large amount of image files

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