Why do people record videos and share them? While the question seems to be simple, user intentions have not yet been investigated for video production and sharing. A general taxonomy would lead to adapted information systems and multimedia interfaces tailored to the users’ intentions. We contribute (1) an exploratory user study with 20 participants, examining the various facets of user intentions for video production and sharing in detail and (2) a novel set of user intention clusters for video production, grounded empirically in our study results. We further reflect existing work in specialized domains (i.e. video blogging and mobile phone cameras) and show that prevailing models used in other multimedia fields (e.g. photography) cannot be used as-is to reason about video recording and sharing intentions.
This paper has been published and presented at WIAMIS 2012.
Authors: Mathias Lux & Jochen Huber
Due to numerous requests I prepared a package showing off a simple indexer and a simple search. Inside there are two classes: Indexer and Searcher. Each of them does what their name suggests.
Indexer takes the first command line argument, interprets it as directory, gets all images from this directory and indexes and stores them in a newly created directory called “index”. Searcher searches in excactly this image index for the query image specified with the first argument.
The sample application employs CEDD and provides an ANT build file. IDEs like NetBeans, Eclipse or IntelliJ IDEA should have no problems importing the sources and using the build.xml file for compiling and running. Arguments can be changed in the build.xml file.
I finally foundsome time to do some minor updates on the developer wiki. Most interesting change is that I added a page describing how to apply result filters to re-rank search results. This can be done with different features or LSA. See the wiki page here. Filtering of result sets can be easily tried with the current SVN version of LireDemo. I also updated the FAQ a bit including some pointers for those who have their first encounter with Java.
Recently I posted binaries and packaged libraries for face detection based on OpenCV an OpenIMAJ here and here. Basically both employ similar algorithms to detect faces in photos. As this is based on supervised classification not only the algorithm but also the employed training set has strong influence on the actual precision (and recall) of results. So out of interest I took a look on how well the results of both libraries are correlated:
imaj_20 1.000 0.933 0.695
imaj_40 0.933 1.000 0.706
opencv_ 0.695 0.706 1.000
Above table shows the Pearson correlation of the face detection algorithm with the default models of OpenIMAJ (with a minimum face size of 20 and 40 pixels) and OpenCV. As can be seen the results correlate, but are not the same. Conclusion is: make sure that you check which one to use for your aplication and eventually train one yourself (as actually recommended by the documentation of both libraries).
This experiment has been done on just 171 images, but experiments with larger data sets have shown similar results.
WIAMIS 2012 has started in the morning and first kenote was Prof. Mubarak Shah from University of Central Florida. He talked about primitives for detection of human actions. Especially the visualization of his ideas and approaches was really great! Currently the retrieval session is going on.
My own presentation on user intentionsin video production is scheduled on Friday as the very last presentation, just before the closing remarks.
Dr. Oge Marques, author of the book Practical Image and Video Processing Using MATLAB is giving a tutorial on Java based visual information retrieval at SIGIR 2012. Oge Marques is Associate Professor in the Department of Computer & Electrical Engineering and Computer Science at Florida Atlantic University. He has been teaching and doing research on image and video processing for more than twenty years, in seven different countries.
In his tutorial, he presents an overview of visual information retrieval (VIR) concepts, techniques, algorithms, and applications. Several topics are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for content-based image retrieval (CBIR) .
Read more & register on the SIGIR 2012 web page (as soon as it is updated).