Abstract book (pdf) - ICPR 2010

ThAT1 Marmara Hall
Object Detection and Recognition - IV Regular Session
Session chair: Lee, Kyoung Mu (Seoul National Univ.)
09:00-09:20, Paper ThAT1.1
Visual Recognition of Types of Structural Corridor Landmarks using Vanishing Points Detection and Hidden Markov
Models
Park, Young-Bin, Hanyang Univ.
Kim, Sung-Su, Hanyang Univ.
Suh, Il Hong, Hanyang Univ.
In this paper, to provide a robot with information relative to structure of its environment, we propose a method to recognize
types of structural corridor landmarks such as T-junction, L-junction, end of the corridor, using vanishing points-based visual
image features and hidden Markov models. Several experimental results are illustrated to emonstrate the validity of the proposed
approach in a real environment.
09:20-09:40, Paper ThAT1.2
Multi-Object Segmentation in a Projection Plane using Subtraction Stereo
Ubukata, Toru, Chuo University / CREST, JST
Terabayashi, Kenji, Chuo Univ.
Moro, Alessandro, Univ. of Trieste
Umeda, Kazunori, Chuo Univ.
We propose a method for multi-object segmentation in a projection plane. Our algorithm requires a stereo camera system
called Subtraction Stereo, which extracts foreground information with a fixed stereo camera. The main contribution of this
paper is how the image sequences that include partial occlusion of the foreground objects can be accurately segmented using
mean shift clustering in real-time processing. The proposed method is suitable for inside a medium-sized environment, such
as a room. Finally, we try to segment the sequences that include occlusion and show the accuracy of the proposed method.
09:40-10:00, Paper ThAT1.3
Transitive Closure based Visual Words for Point Matching in Video Sequence
Bhat, Srikrishna, INRIA
Berger, Marie-Odile, INRIA
Simon, Gilles, Nancy-Univ.
Sur, Frédéric, INPL / INRIA Nancy Grand Est
We present Transitive Closure based visual word formation technique for obtaining robust object representations from
smoothly varying multiple views. Each one of our visual words is represented by a set of feature vectors which is obtained
by performing transitive closure operation on SIFT features. We also present range-reducing tree structure to speed up the
transitive closure operation. The robustness of our visual word representation is demonstrated for Structure from Motion
(SfM) and location identification in video images.
10:00-10:20, Paper ThAT1.4
Constrained Energy Minimization for Matching-Based Image Recognition
Gass, Tobias, RWTH Aachen Univ.
Dreuw, Philippe, RWTH Aachen Univ.
Ney, Hermann, RWTH Aachen Univ.
We propose to use energy minimization in MRFs for matching-based image recognition tasks. To this end, the Tree-
Reweighted Message Passing algorithm is modified by geometric constraints and efficiently used by exploiting the guaranteed
monotonicity of the lower bound within a nearest-neighbor based classification framework. The constraints allow for a
speedup linear to the dimensionality of the reference image, and the lower bound allows to optimally prune the nearestneighbor
search without loosing accuracy, effectively allowing to increase the number of optimization iterations without an
effect on runtime. We evaluate our approach on well-known OCR and face recognition tasks and on the latter outperform
current state-of-the-art.
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