• ETRI Journal
• /
• v.36 no.4
• /
• pp.662-672
• /
• 2014

Human action recognition is used in areas such as surveillance, entertainment, and healthcare. This paper proposes a system to recognize both single and continuous human actions from monocular video sequences, based on 3D human modeling and cyclic hidden Markov models (CHMMs). First, for each frame in a monocular video sequence, the 3D coordinates of joints belonging to a human object, through actions of multiple cycles, are extracted using 3D human modeling techniques. The 3D coordinates are then converted into a set of geometrical relational features (GRFs) for dimensionality reduction and discrimination increase. For further dimensionality reduction, k-means clustering is applied to the GRFs to generate clustered feature vectors. These vectors are used to train CHMMs separately for different types of actions, based on the Baum-Welch re-estimation algorithm. For recognition of continuous actions that are concatenated from several distinct types of actions, a designed graphical model is used to systematically concatenate different separately trained CHMMs. The experimental results show the effective performance of our proposed system in both single and continuous action recognition problems.

• Journal of Industrial Technology
• /
• v.16
• /
• pp.257-265
• /
• 1996

When machining of a free-form surface with a ball endmill it is very important to select proper cutting conditions considering the geometrical shape of a workpiece to make the production more effective and reduce the machining time. Even though the same cutting conditions and materials are used, the cutting system of different geometry part machining shows the different static/dynamic characteristics. In this study, through various cutting experiments, we can construct the data base of stable cutting conditions for the machining of a Zine Alloy. We can get some relational plots between the optimal feedrates and classified shape features and parameters. On the basis of these results, we can develop the feedrate optimization program OptiCode. The developed program make it possible to reduce the cutting time and increase the machining accuracies.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.11
• /
• pp.103-111
• /
• 2011

In this paper, we propose a Geometrical Centroid Contour Distance(GCCD) which is described by shape signature based on contour sequence. The proposed method uses geomertrical relation features instead of the absolute angle based features after it was normalized and aligned with dominant feature of the shape. Experimental result with MPEG-7 CE-Shape-1 Data Set reveals that our method has low time/spatial complexity and scale/rotation robustness than the other methods, showing that the precision of our method is more accurate than the conventional desctiptors. However, performance of the GCCD is limited with concave and complex shaped objects.