Kyu-Min Kyung

Background subtraction based object extraction for Time-of-Flight sensor

This paper presents a moving object extraction method using background subtraction techniques for Time-of-Flight sensor. Time-of-Flight sensor obtains two different types of data at the same time. One is depth data representing the distance to objects and another is intensity data representing the confidence level of depth data. After each reference background model is constructed for depth and intensity data, each foreground object map is obtained for depth and intensity data by comparing to its reference background model. Final foreground objects are extracted by combining two foreground object maps to remove noise data. The simulation results with MESA SR4000 show that the proposed method extracts moving objects accurately.

New biometrics-acquisition method using time-of-flight depth camera

This paper introduces basic concept of biometrics acquisition method using time-of-flight (ToF) depth camera, taking the advantages of obtaining 3D data and near infrared (NIR) image simultaneously. This concept can be applied to various biometrics, such as touch-less or multimodal biometrics.

Fast and efficient method to suppress depth ambiguity for Time-of-Flight sensors

This paper presents a fast and efficient method to suppress (i.e. not to unwrap but only to remove) depth ambiguity for Time-of-Flight sensors. Depth and amplitude data for each pixel is obtained by correlating the emitted signal and the reflected signal. Each depth data is classified according to predetermined depth levels and the average amplitude with neighboring pixels is used to determine ambiguous depth beyond the maximum measurable depth. Different amplitude threshold values are used according to the classified depth for the accurate suppression. The proposed method does not require complex computation for edge detection and object segmentation as compared to object segmentation based method. The comparison simulation results demonstrate that the proposed method suppresses the depth ambiguity effectively.