X-View: Graph-Based Semantic Multi-View Localization
نویسندگان
چکیده
منابع مشابه
Watertight Multi-view Reconstruction Based on Volumetric Graph-Cuts
This paper proposes a fast 3D reconstruction approach for efficiently generating watertight 3D models from multiple short baseline views. Our method is based on the combination of a GPU-based plane-sweep approach, to compute individual dense depth maps and a subsequent robust volumetric depth map integration technique. Basically, the dense depth map values are transformed to a volumetric grid, ...
متن کاملMulti-view Clustering with Adaptively Learned Graph
Multi-view clustering, which aims to improve the clustering performance by exploring the data’s multiple representations, has become an important research direction. Graph based methods have been widely studied and achieve promising performance for multi-view clustering. However, most existing multi-view graph based methods perform clustering on the fixed input graphs, and the results are depen...
متن کاملSemantic Multi-View model for Low-Power
Power is an important concern in embedded systems. Reduction of power consumption is achieved by balancing the control of multiple domains: switching power, reducing or increasing voltage and changing the frequency on system sections. Model-Driven Engineering gives tools to model the interactions of these domains. In this work, we propose to use MARTE combined to UPF concepts to capture the str...
متن کاملCross-view and multi-view gait recognitions based on view transformation model using multi-layer perceptron
Gait has been shown to be an efficient biometric feature for human identification at a distance from a camera. However, performance of gait recognition can be affected by various problems. One of the serious problems is view change which can be caused by change of walking direction and/or change of camera viewpoint. This leads to a consequent difficulty of across-view gait recognition where pro...
متن کاملError-Based Multi-View Triangulation
A comprehensive uncertainty, baseline, and noise analysis in computing 3D points using a recent L1-based triangulation algorithm is presented. This method is shown to be not only faster and more accurate than its main competitor, linear triangulation, but also more stable under noise and baseline changes. A Monte Carlo analysis of covariance and a confidence ellipsoid analysis were performed ov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Robotics and Automation Letters
سال: 2018
ISSN: 2377-3766,2377-3774
DOI: 10.1109/lra.2018.2801879