Jiyeun Kim

Learning based ensemble segmentation of anatomical structures in liver ultrasound image

Automatic segmentation of anatomical structure is crucial for computer aided diagnosis and image guided online treatment. In this paper, we present a novel approach for fully automatic segmentation of all anatomical structures from a target liver organ in a coherent framework. Firstly, all regional anatomical structures such as vessel, tumor, diaphragm and liver parenchyma are detected simultaneously using random forest classifiers. They share the same feature set and classification procedure. Secondly, an efficient region segmentation algorithm is used to obtain the precise shape of these regional structures. It is based on level set with proposed active set evolution and multiple features handling which achieves 10 times speedup over existing algorithms. Thirdly, the liver boundary curve is extracted via a graph-based model. The segmentation results of regional structures are incorporated into the graph as constraints to improve the robustness and accuracy. Experiment is carried out on an ultrasound image dataset with 942 images captured with liver motion and deformation from a number of different views. Quantitative results demonstrate the efficiency and effectiveness of the proposed algorithm.

An extensible framework for facial motion tracking

Facial motion tracking is a challenging task because of highly flexible head pose and facial expression. An extensible tracking framework is proposed in this paper. Within the framework, proper models are selected according to requirements and restrictions of the application, and different trackers can be constructed to handle different tasks. Experimental result shows that our tracker outperforms the existing commercial software.

User-centric and remote content browsing for mobile devices

In this paper, we propose a provision of user-centric mobile media album system and albuming functions to support it. For the system, we are considering both a stand-alone type implementation and a PC bundle type implementation. The main idea of the user-centric and remote content browsing for albuming functions is to enable users to organize and browse their photos along the semantically meaningful axes that are event, person-identity, and category while the highlights of video contents are processed by PC and easily downloaded and watched on mobile devices. Experiment results demonstrate that the proposed method would be useful to browse photos and video clips.

Easy and effective indexing and browsing schemes for digital photo album application

In this paper, we propose a method to cluster digital home photos associated with user-centric functionalities, which are event/situation based photo clustering, category based photo clustering, and person-identity based photo clustering and indexing. The main idea of the user-centric photo album is to enable users to organize and browse their photos along the semantically meaningful axes that are situation, category, and person-identity. Experiment results showed that the proposed method would be useful to organize a photo album based on human perception.