Abstract book (pdf) - ICPR 2010

Perdoch, Michal, Czech Tech. Univ. in Prague
Chum, Ondrej, Czech Tech. Univ. in Prague
Detection of repetitive patterns in images has been studied for a long time in computer vision. This paper discusses a
method for representing a lattice or line pattern by shift-invariant descriptor of the repeating element. The descriptor overcomes
shift ambiguity and can be matched between different a views. The pattern matching is then demonstrated in retrieval
experiment, where different images of the same buildings are retrieved solely by repetitive patterns.
13:30-16:30, Paper WeBCT9.19
An Approach for Recognizing Text Labels in Raster Maps
Chiang, Yao-Yi, USC ISI
Knoblock, Craig, USC ISI
Text labels in raster maps provide valuable geospatial information by associating geographical names with geospatial locations.
Although present commercial optical character recognition (OCR) products can achieve a high recognition rate
on documents containing text lines of the same orientation, text recognition on raster maps is challenging due to the varying
text orientations and the overlap of text labels. This paper presents a text recognition approach that focuses on locating individual
text labels in the map and detecting their orientations to then leverage the horizontal text recognition capability
of commercial OCR software. We show that our approach detects accurate string orientations and achieves 96.2% precision
and 94.7% recall on character recognition and 80.6% precision and 84.1% recall on word recognition.
13:30-16:30, Paper WeBCT9.20
Local Visual Pattern Indexing for Matching Screenshots with Videos
Poullot, Sebastien, National Inst. of Informatics
Satoh, Shin’Ichi, National Inst. of Informatics
In this paper a particular issue is addressed: matching still images (screen shots) with videos. A content-based similarity
search approach using image queries is proposed. A fast method based on local visual patterns both for matching and indexing
is employed. But we argue that using every frames may limit the scalability of the approach. Therefore only
keyframes are extracted and used. The main contribution of this paper is an investigation over the trade-off between accuracy
and scalability using different keyframe rates for sampling the video database. This trade-off is evaluated on a
ground truth using a large reference video database (1000 hours).
13:30-16:30, Paper WeBCT9.21
Suggesting Songs for Media Creation using Semantics
Joshi, Dhiraj, Kodak Res. Lab.
Wood, Mark, Eastman Kodak Company
Luo, Jiebo, -
In this paper, we describe a method for matching song lyrics with semantic annotations of picture collections in order to
suggest songs that reflect picture content in lyrics or genre. Picture collections are first analyzed to extract a variety of semantic
information including scene type, event type, and geospatial information. When aggregated over a picture collection,
this semantic information forms a semantic signature of the collection. Typical picture collections in our scenario consist
of photo subdirectories in which people store pictures of a place, activity, or event. Picture collections are expected to
contain coherent semantic content describing in part or whole the event or activity they depict. The semantic signature of
a picture collection is compared against song lyrics using a WordNet expansion based text matching to find songs relevant
to the collection. We present interesting song suggestions, compare and contrast scenarios with human versus machine labels,
and perform a user study to validate the usefulness of the proposed method. The proposed method will be a useful
tool to support user media creation.
13:30-16:30, Paper WeBCT9.22
Color Feature based Approach for Determining Ink Age in Printed Documents
Halder, Biswajit, Mallabhum Inst. of Tech.
Garain, Utpal, Indian Statistical Inst.
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