Outbreak of neuropathogenic equid herpesvirus 1 causing abortions in Yili horses of Zhaosu, North Xinjiang, China.

Background: EHV-1 is one of the most serious viral pathogens that frequently cause abortion in horses around the world. However, so far, relatively little information is available on EHV-1 infections as they occur in China. In January 2021, during an abortion storm which occurred in Yili horses at the Chinese State Studs of Zhaosu (North Xinjiang, China), 43 out of 800 pregnant mares aborted.

On-device mobile visual location recognition by using panoramic images and compressed sensing based visual descriptors.

Mobile Visual Location Recognition (MVLR) has attracted a lot of researchers' attention in the past few years. Existing MVLR applications commonly use Query-by-Example (QBE) based image retrieval principle to fulfill the location recognition task. However, the QBE framework is not reliable enough due to the variations in the capture conditions and viewpoint changes between the query image and the database images.

Real-time camera pose estimation for wide-area augmented reality applications.

Achieving accurate registration between real and synthetic worlds is one of augmented reality's biggest challenges. A real-time camera-pose estimation method, based on multiple maps and local bundle adjustment, enables the registration to work without prior knowledge of natural scenes. This method can significantly enhance AR systems' usability.

Fast scene recognition and camera relocalisation for wide area augmented reality systems.

This paper focuses on online scene learning and fast camera relocalisation which are two key problems currently limiting the performance of wide area augmented reality systems. Firstly, we propose to use adaptive random trees to deal with the online scene learning problem. The algorithm can provide more accurate recognition rates than traditional methods, especially with large scale workspaces.

Registration Combining Wide and Narrow Baseline Feature Tracking Techniques for Markerless AR Systems.

Augmented reality (AR) is a field of computer research which deals with the combination of real world and computer generated data. Registration is one of the most difficult problems currently limiting the usability of AR systems. In this paper, we propose a novel natural feature tracking based registration method for AR applications.