In this paper, we investigate how to incorporate spatial and/or temporal contextual information into classical histogram features with the aim of boosting visual classification p...
Linear discriminant analysis (LDA) has been successfully applied into computer vision and pattern recognition for effective feature extraction. High-dimensional objects such as im...
We present a Resolution-Invariant Image Representation (RIIR) framework in this paper. The RIIR framework includes the methods of building a set of multi-resolution bases from tra...
In this paper, we present a systematic framework for recognizing realistic actions from videos “in the wild.” Such unconstrained videos are abundant in personal collections as...
We propose a fast and robust CV-SLAM (Ceiling Vision –based Simultaneous Localization and Mapping) technique using a single ceiling vision sensor. The proposed algorithm is suita...
Woo Yeon Jeong (Seoul National University), Kyoung...
This paper deals with feature matching and segmentation of common objects in a pair of images, simultaneously. For the feature matching problem, the matching likelihoods of all fea...
Tae Hoon Kim (Seoul National University), Kyoung M...
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
We propose a novel stochastic graph matching algorithm based on data-driven Markov Chain Monte Carlo (DDMCMC) sampling technique. The algorithm explores the solution space efficien...
In this paper, we present a method that recognizes single or multiple common actions between a pair of video sequences. We establish an energy function that evaluates geometric and...
Young Min Shin (Seoul National University), Minsu ...