Heon-Hui Kim

Automatic Generation of Conversational Robot Gestures for Human-friendly Steward Robot

Recently, in service robotics area, increasing attention is being paid on interaction capability of robot for human-being as well as its task performing capability. In this paper, in particular, an automatic gesture generation methodology for conversational interaction of service robots is presented toward more human-friendly human-robot interaction. From the survey on the results in the psychology field, we first categorized the target gestures into the three types of gestures, which are basic, supplementary/emphasizing, and finishing/interconnective gestures with their corresponding unit gesture components. Then, a set of mapping rules have been extracted for gesture generation based on observing human behavioral patterns during conversation, by means of morpheme decomposition and analysis. From the given text input in Korean, the proposed system tries to generate robotic gestures, which consist of the head and the arm motions, by gesture selection and motion scheduling schemes. Finally, we discuss on the effectiveness of the proposed system with the simulated motions of robot as an initial attempt to apply in a practical system.

A User Adaptation Method for Hand Shape Recognition Using Wrist-Mounted Camera

This paper proposes a robust hand segmentation method using view-invariant characteristic of a wrist-mounted camera, and deals with a hand shape recognition system based on segmented hand information. We actively utilize the advantage of the proposed camera device that provides view-invariant images physically, and segment hand region using a Bayesian rule based on adaptive histograms. We construct HSV histograms from RGB histograms, and update HSV histograms using hand region information from a current image. We also propose a user adaptation method by which hand models gradually approach user-dependent models from user-independent models as the user uses the system. The proposed method was evaluated using 16 Korean manual alphabet, and we obtained increases of 27.91% in recognition success rate.

Walking Phase Recognition for People with Lower Limb Disability

This paper presents a total solution on EMG signal-based walking phase recognition for people with lower limb disability. Various environmental factors such as sensed location, walking speed, and ground inclination are taken into consideration in all the phases of signal sensing, feature extraction, feature selection, and classification. Based on analysis on fourteen well-known feature extraction methods in varying environmental situation, this paper proposes a methodology for selecting a good feature set, and then demonstrates effectiveness of the proposed approach with the classification results.

Buffer Management Scheme for Interactive Video Streaming

In this paper, we propose a buffer management scheme suitable for interactive multimedia services. We consider a typical delay optimization environment so that receiver buffer lengths vary according to the round trip time estimation. In this environment, we propose an optimization technique for minimizing the loss of information that may occur when a reduced buffer length forces I/P/B frames in the buffer to drop. We modeled our problem as a Knapsack Problem for which we used dynamic programing in order to find an approximate solution. The proposed technique is compared with the existing buffer management techniques. Through simulation studies, we found that our approach could increase PSNR, which is important to video quality.