Jun Ohmiya

Chapter generation for digital video recorder based on perceptual clustering

We propose a novel automatic chapter generating technique for digital video recorder (DVR) based on a perceptual clustering. Clustering with two-staged hierarchy is introduced for the first time, showing better performance than previous approaches without requiring any rule-based processes like recognition or modeling. Implementation into our DVR is planned.

Probe localization using structure from motion for 3D ultrasound image reconstruction

This paper proposes an accurate ultrasound probe localization method for 3D US image reconstruction. The proposed method consists of (i) feature tracking of a video sequence and (ii) camera pose estimation using structure from motion (SfM). SfM is used to reconstruct 3D point clouds from multiple-view images and simultaneously estimate each camera position. To apply SfM to a video sequence, the accurate method is required to track features between adjacent frames. We employ a sub-pixel image matching technique using Phase-Only Correlation (POC) for feature tracking. POC is a technique of image matching using phase components in the Fourier transforms of images. Through a set of experiments, we demonstrate that the proposed method can estimate the location of the US probe with about 2mm error for the probe travel distance of 150–200mm.

Image stabilization algorithm for video with large image fluctuation

We propose an image stabilization system for video with large image fluctuation by estimating and correcting translation and rotation from the video. The fluctuation is handled ,separately ,as ,relative ,inter-frame ,motion ,and ,absolute intra-frame information, in order to suppress large fluctuation in the video sequence efficiently.

A Probe-Camera System for 3D Ultrasound Image Reconstruction

This paper proposes a probe-camera system for 3D ultrasound (US) image reconstruction with probe-camera calibration and probe localization methods. The probe-camera calibration method employs an existing US phantom for convenience with a simple procedure. The probe localization method employs structure from motion (SfM) to estimate the camera motion. SfM is used to reconstruct 3D point clouds from multiple-view images and simultaneously estimate each camera position. Through experiments using the developed system, we demonstrate that the proposed method exhibits good performance to reconstruct 3D US volume.

Fully Automatic Detection of the Carotid Artery from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features

We propose a fully automatic method for detecting the carotid artery from volumetric ultrasound images as a preprocessing stage for building three-dimensional images of the structure of the carotid artery. The proposed detector utilizes support vector machine classifiers to discriminate between carotid artery images and non-carotid artery images using two kinds of LBP-based features. The detector switches between these features depending on the anatomical position along the carotid artery. The detector narrows the search area for detection in consideration of the three-dimensional continuity of the carotid artery to suppress false positives and improve processing speed. We evaluate our proposed method using actual clinical cases. Accuracies of detection are 100 %, 87.5 % and 68.8 % for the common carotid artery, internal carotid artery, and external carotid artery sections, respectively. We also confirm that detection can be performed in real time using a personal computer.