Chil-Woo Lee

Automatic recognition of human facial expressions

The paper presents a new idea for detecting an unknown human face in input imagery and recognizing his/her facial expression represented in the deformation of the two dimensional net, called potential net. The method deals with the facial information, faceness and expressions, as an overall pattern of the net activated by edges in a single input image of face, rather than from changes in the shape of the facial organs or their geometrical relationships. We build models of facial expressions from the deformation patterns in the potential net for face images in the training set of different expressions and then project them into emotion space. Expression of an unknown subject can be recognized from the projection of the net for the image into the emotion space. The potential net is further used to model the common human face. The mosaic method representing energy in the net is used as a template for finding candidates for the face area and the candidates are verified their faceness by projecting them into emotion space in order to select the finalist. Precise location of the face is determined by the histogram analysis of vertical and horizontal projections of edges.<<ETX>>

HCI(Human Computer Interaction) Using Multi-touch Tabletop Display

In this paper, we describe the development of multi-touch tabletop display system and the classification of hand gesture commands for interacting with our system. And also, we analyze the suitability for interactive tabletop in light of the respective input and output degrees of freedom, as well as the precision and completeness provided by each. Our system is based on FTIR (frustrated total internal reflection) principle and hand gestures for necessary instructions are predefined using position sensing and tracking of multi-touch points and the number of fingertips. The system consists of two beam-projectors, diffuser film, infrared cameras and large acrylic screen that attached infrared LED. In recognition process, gesture commands are analyzed by comparing with predefined gesture instructions according to the number of contacted fingertips, Euclidean distance and angles between two bright spots. In this paper, vision based tabletop display system that we proposed provides much advantages understanding human and computer interaction. Also the efficiency of proposed method can be proved through controlling Google-earth.

Automatic segmentation of the liver in CT images using the watershed algorithm based on morphological filtering

Liver segmentation is one of the most basic and important parts in computer-aided diagnosis for liver CT. Although various segmentation methods have been proposed for medical imaging, most of them generally do not perform well in segmenting the liver from CT images because of surface features of the liver and difficulty of discrimination from other adjacent organs. In this paper, we propose a new scheme for automatic segmentation of the liver in CT images. The pro-posed scheme is carried out on region-of-interest (ROI) blocks that include regions of the liver with high probabilities. The ROI approach saves unnecessary computational loss in finding the accurate boundary of the liver. The proposed method utilizes the composition of morphological filters with a priori knowledge, such as the general location or the approximate intensity of the liver to detect the initial boundary of the liver. Then, we make the gradient image with the weight of an initial liver boundary and segment the liver region by using an immersion-based watershed algorithm in the gradient image. Finally, a refining process is carried out to acquire a more accurate liver region.

Detection and pose estimation of human face with synthesized image models

This paper presents a new method for detecting a human face, and estimating its pose while tracking it in real image sequences. The virtue of the method is that parameterized qualitative features derived from a lot of sampled facial images are introduced in the detection process, and in the face tracking process, some temporary model images of the face with various poses are synthesized by a texture mapping technique and utilized. While tracking the detected face, many model images are accumulated and the pose of the human face is estimated as a linear combination of correlations between the models.

Contextual decomposition of multi-label images

Most research on image decomposition, e.g. image segmentation and image parsing, has predominantly focused on the low-level visual clues within single image and neglected the contextual information across different images. In this paper, we present a new perspective to image decomposition piloted by the multi-labels associated with individual images. Observing that the context information (i.e., local label representations of the same label are similar while those from different labels are dissimilar) exists across different images, we propose to perform image decomposition in a collective way, and then the image decomposition problem is formulated as an optimization which maximizes inter-label difference and at the same time minimizes intra-label difference of the target label representations. Such contextual image decomposition has a wide variety of applications, among which the two exemplary ones are: 1) multi-label image annotation in which the sparse coding of a query image over the bases consisting of all learned label representations naturally produces the multi-label annotation, and 2) label ranking in which the annotated labels are re-ordered according to the sparse coding coefficients on those learned label representations. It is worth noting that these two applications can be performed simultaneously via the label propagation process in sparse coding.

Dual interactions between multi-display and smartphone for collaborative design and sharing

We present a new way of dual interactions between multi-display and smartphone for collaborative design review and sharing among multi-users. It provides individual and cooperative interactions in immersive and non-immersive environments to decouple private and public spaces between multi-display and smartphone. Thus, it can provide different views among multiusers and make them communicate with each other more adaptively according to the shared contents. We will show implementation results by demonstrating digital product review and multimedia interactions among multi-users.

Real Time Moving Object Tracking by Particle Filter

Robust and real time moving object tracking is a tricky job in computer vision problems. Particle filtering has been proven very successful for non-Gaussian and non-linear estimation problems. In this paper, we first try to develop a color based particle filter. In this approach, the object tracking system relies on the deterministic search of window, whose color content matches a reference histogram model. A simple HSV histogram-based color model is used to develop our observation system. Secondly and finally, we describe a new approach for moving object tracking with particle filter by shape information. The shape similarity between a template and estimated regions in the video scene is measured by their normalized cross-correlation of distance transformed image. Our observation system of particle filter is based on shape from distance transformed edge features. Template is created instantly by selecting any object from the video scene by a rectangle. Experimental results have been presented to show the effectiveness of our proposed system.

Multi-touch interaction for table-top display

In this paper, we describe a system of multi-touch tabletop display and its control algorithm for Google-earthTM that utilizes hand gesture as mouse free interaction. The system adopts well known FTIR technique. The hand gesture of necessary instruction is predefined according to the number, position, and movement of the fingertips which are obtained from multi-touch of a single user. The system consists of a beam-projector and an acrylic screen attaching infrared LED as light source, and an infrared camera for capturing the fingertip image. Input image is preprocessed with simple morphological method to remove the noise and to determine the fingertip region. In recognition process, gesture commands are recognized by comparing the preprocessed image with predefined gesture model of fingertips. In detail, firstly the number of the spot; fingertip mark, angles among the spots, and Euclidean distance between two spots are calculated, and then the values are compared with the information of the model. The effectiveness of the system can be proved through the experimental results.

A method of real-time gesture recognition for interactive systems

This paper presents a new method for real-time gesture recognition and its application. The key idea of the method is that we use multiple template models for specific feature parts of body such as arms and estimate the pose of this part by considering similarities of an input image to the models. To calculate the similarity for the part, we developed maskable template model (MTM) with which both masking and template matching are done simultaneously. As an application of this method, we realize a real-time interactive system, gesture game system, which can activate the characters of video game by gestures in real-time.

Real-time gesture recognition using Maskable Template Model

We describe a new method for real-time gesture recognition and its application. The key idea of the method is that we use multiple template models for specific feature parts of the body such as arms and estimate the pose of this part by comparing similarities of an input image to the models. To calculate the similarity for the part, we developed the Maskable Template Model (MTM) with which both masking and template matching operations are simultaneously completed. As an application of this method, we realize a real-time interactive system, Gesture Game System, which can activate the characters of a video game by gestures in real-time.