Soochahn Lee

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The availability of accurate depth cameras have made real-time human pose estimation possible; however, there are still demands for faster algorithms on low power processors. This paper introduces 1000 frames per second pose estimation method on a single core CPU. A large computation gain is achieved by random walk sub-sampling. Instead of training trees(More)
1047-3203/$ see front matter 2010 Elsevier Inc. A doi:10.1016/j.jvcir.2010.04.005 q This research was supported by Basic Science Re National Research Foundation of Korea (NRF) funded Science and Technology (20090053539). * Corresponding author. ** Corresponding author. E-mail addresses: (S. Lee) (S.U. Lee).(More)
In this paper, we propose a new 3-D model retrieval system using the Aspect-Transition Descriptor which is based on the aspect graph representation [1, 2] approach. The proposed method differs from the conventional aspect graph representation in that we utilize transitions as well as aspects. The process of generating the Aspect-Transition Descriptor is as(More)
In this paper, we present a novel cascaded classification framework for automatic detection of individual and clusters of microcalcifications (μC). Our framework comprises three classification stages: i) a random forest (RF) classifier for simple features capturing the second order local structure of individual μCs, where non-μC pixels in the target(More)
In this paper, we propose a fully automatic method to segment bone compartments in magnetic resonance (MR) images of knee joints gathered from a public database for research on knee osteoarthritis (OA), the osteoarthritis initiative (OAI). Considering the fixed scanning parameters which include position and flexion of the knee joint, the proposed method(More)
In this paper, to evaluate the performance of object recognition algorithms, we propose a new evaluation framework by synthesizing natural scenes based on the Amsterdam Library of Object Images [1]. Here, the evaluation of an object recognition algorithm has the basis on searching an object in a synthetic scene. More specifically, an object is selected, and(More)
We present multiple random forest methods for human pose estimation from single depth images that can operate in very high frame rate. We introduce four algorithms: random forest walk, greedy forest walk, random forest jumps, and greedy forest jumps. The proposed approaches can accurately infer the 3D positions of body joints without additional information(More)