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From: | David Squire |
Subject: | Re: [help-GIFT] gift algorithms - separate normalization and CIDF |
Date: | Sat, 07 Jun 2003 09:00:50 +1000 |
User-agent: | Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.3) Gecko/20030312 |
Mika Rummukainen wrote:
All that "separate normalization" means is that the similarity score is first calculated for each feature group separately, each feature group score is normalized, and then they are added to get the final score, e.g.Hi there, I've been wondering for a while now for couple of questions. Question 1: How does GIFT perform the weighting of features with different algorithms?From articles (Content-based query of image databases,inspirations from textretrieval: inverted files, frequency-based weights and relevance feedback and Content-based query of image databases: inspirations from text retrieval (Pattern Recognition Letters 21)) I managed to find some information but I assume the equations how scores arecalculated (after relevance feedback) for every image are for CIDF only.Now I'd like to know how Separate Normalization performs its weighting. From "Strategies for positive and negative relevance feedback in image retrieval" I found a "Separately weighted feedback" - is this how separate normalization isperformaing?Question 2: This makes me think that when GIFT uses separate normalization, it first uses CIDF algorithm to weight the features and then uses separate normalization to weight even more the weighted features calculated by CIDF. Am I completely on a wrong path here?
FinalSimilarity = 0.25*ColourHistogramSimilarity + 0.25*ColourBlockSimilarity + 0.25*TextureHistogramSimilarity + 0.25*TextureBlockSimilarity
where all of ColourHistogramSimilarity, ColourBlockSimilarity, TextureHistogramSimilarity and TextureBlockSimilarity have been normalized to the range [0,1]. This prevents feature groups that have more features completely dominating the total score.
Question 3: How is the similarity of images calculated with both algorithms if there wouldAll query similarities are calculated the same way, whether there is relevance feedback or not. A single image query simply has one relevant image.be no relevance feedback?
Cheers, David -- Dr. David McG. Squire, Postgraduate Research Coordinator (Caulfield), Computer Science and Software Engineering, Monash University, Australia http://www.csse.monash.edu.au/~davids/
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