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The ability to recognize objects and to localize them precisely is essential in all service robotic applications. One of the main challenges for service robots during operation lies in the handling of unavoidable uncertainties which originate from model and sensor inaccuracies and are characteristic for realistic application scenarios. Robustness under real world conditions can only be achieved when...
In this article, we describe a system that estimates the position and orientation of a calibrated camera. For better estimation accuracy, artificial markers made up of infrared LEDs are placed in certain pattern onto the ceiling of a room. A 3D reconstruction process is first performed offline so that the coordinates of all LEDs within a unified world frame are determined. This process, based on incremental...
This paper explores the idea of extracting three dimensional features from a previously recorded video, in an attempt to provide three dimensional information about a video clip in order to improve the performance of various video analysis tasks. Although video analysis is a very prevalent area of research, the use of 3D features is scarce in the literature due to the inherent difficulties associated...
We present a fast and memory efficient method for localizing a mobile user's 6DOF pose from a single camera image. Our approach registers a view with respect to a sparse 3D point reconstruction. The 3D point dataset is partitioned into pieces based on visibility constraints and occlusion culling, making it scalable and efficient to handle. Starting with a coarse guess, our system only considers features...
This paper addresses the problem of human action matching in outdoor sports broadcast environments, by analysing 3D data from a recorded human activity and retrieving the most appropriate proxy action from a motion capture library. Typically pose recognition is carried out using images from a single camera, however this approach is sensitive to occlusions and restricted fields of view, both of which...
We present a structure-from-motion (SfM) pipeline for visual 3D modeling of a large city area using 360?? field of view Google Street View images. The core of the pipeline combines the state of the art techniques such as SURF feature detection, tentative matching by an approximate nearest neighbour search, relative camera motion estimation by solving 5-pt minimal camera pose problem, and sparse bundle...
Despite leaps in motion capture technology, the dichotomy between unencumbered vision-based motion recovery and the prevailing marker-assisted motion capture solution remains largely pertinent. This paper bridges the gap by introducing an attachment-free, full-body motion capture technique that employs multiple high-speed cameras and a customized bodysuit. The flexible bodysuit allows free movements...
This paper investigates a human body posture estimation method based on the back projection of human silhouette images extracted from multi-camera images. The multi-camera system is based on a server-client system with local network of 1000 Base-T to achieve a voxel 3D reconstruction of human body posture in real-time. In order to extract significant points of the human body such as head, neck, shoulders,...
A fast 3D model reconstruction methodology is desirable in many applications such as urban planning, training, and simulations. In this paper, we develop an automated algorithm for texture mapping oblique aerial images onto a 3D model generated from airborne light detection and ranging (LiDAR) data. Our proposed system consists of two steps. In the first step, we combine vanishing points and global...
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