Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy

Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy

Gastroscopic examination is one of the most common methods for gastric disease diagnosis. In this paper, a multitarget tracking approach is proposed to assist endoscopists in identifying lesions under gastroscopy. This approach analyzes numerous preobserved gastroscopic images and constructs a gastroscopic image graph. In this way, the deformation registration between gastroscopic images is reg...

Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application

Reliable and efficient perception and reasoning in dynamic and densely cluttered environments are still major challenges for driver assistance systems. Most of today’s systems use target tracking algorithms based on object models. They work quite well in simple environments such as freeways, where few potential obstacles have to be considered. However, these approaches usually fail in more comp...

Trellis Structure Approach to Multitarget Tracking

In this paper we address sequential multitarget tracking for Radar applications. Specifically, we consider the problem of associating location measurement data over time to form estimates of multiple tracks. The algorithmic approach we employ is sequential and very flexible in that it can handle missed detections, false alarms, track initiation, and number-of-track estimation, while employing m...

Passive multitarget tracking with cameras

This paper considers large areas surveillance and 3D tracking with passive data, obtained here by geographically distributed cameras. The first step, at a camera level, is to detect moving objects in the video sequence and we propose a very simple, fast and efficient approach: a pixel level background subtraction technique to segment foreground pixels and a region level process where segmented ...

Technique and Method of Use of Sternberg's Gastroscopy and Gastroscopic Treatment