Abstract: A method for detecting a target molecule in a sample includes providing a capture species immobilized on a fixed surface; exposing the immobilized capture species to the sample to bind the target molecule; exposing the bound target molecule to a reporter complex to bind the reporter complex to the bound target molecule; and imaging the fixed surface to count the number of the reporter complexes or the number of an imageable product derived from each reporter complex. In an aspect, the signal of the bound target molecule can be amplified to provide an amplified signal that is then exposed to the reporter complex.

Abstract: Described herein are systems and methods that improve the success rate of relocalization and eliminate the ambiguity of false relocalization by exploiting motions of the sensor system. In one or more embodiments, during a relocalization process, a snapshot is taken using one or more visual sensors and a single-shot relocalization in a visual map is implemented to establish candidate hypotheses. In one or more embodiments, the sensors move in the environment, with a movement trajectory tracked, to capture visual representations of the environment in one or more new poses. As the visual sensors move, the relocalization system tracks various estimated localization hypotheses and removes false ones until one winning hypothesis. Once the process is finished, the relocalization system outputs a localization result with respect to the visual map.

Abstract: A simultaneously localization and dense three-dimensional reconstruction method, being capable of processing rapid motion and frequent closing of a loop in a robust manner, and operating at any time in a large-scale scene. Provided by the method is a key frame-based simultaneous localization and map construction framework. First, depth and color information are used simultaneously, and the framework may operate on central processing unit (CPU) at high speed based on localization of the key frame, and operate in challenging scene in robust manner. To reduce accumulated errors, the method introduces increment bundle adjustment, which may greatly reduce an operation amount and enable local and global bundle adjustment to be completed in a unified framework. Secondly, provided by the method is a key frame-based fusion method, and a model may be generated online and a three-dimensional model may be updated in real time during adjustment of the key frame's pose.

Abstract: A method for simultaneous localization and mapping is provided, which can reliably handle strong rotation and fast motion. The method provided a simultaneous localization and mapping algorithm framework based on a key frame, which can support rapid local map extension. Under this framework, a new feature tracking method based on multiple homography matrices is provided, and this method is efficient and robust under strong rotation and fast motion. A camera orientation optimization framework based on a sliding window is further provided to increase motion constraint between successive frames with simulated or actual IMU data. Finally, a method for obtaining a real scale of a specific plane and scene is provided in such a manner that a virtual object is placed on a specific plane in real size.

Abstract: Described herein are systems and methods that improve the success rate of relocalization and eliminate the ambiguity of false relocalization by exploiting motions of the sensor system. In one or more embodiments, during a relocalization process, a snapshot is taken using one or more visual sensors and a single-shot relocalization in a visual map is implemented to establish candidate hypotheses. In one or more embodiments, the sensors move in the environment, with a movement trajectory tracked, to capture visual representations of the environment in one or more new poses. As the visual sensors move, the relocalization system tracks various estimated localization hypotheses and removes false ones until one winning hypothesis. Once the process is finished, the relocalization system outputs a localization result with respect to the visual map.

Abstract: A simultaneously localization and dense three-dimensional reconstruction method, being capable of processing rapid motion and frequent closing of a loop in a robust manner, and operating at any time in a large-scale scene. Provided by the method is a key frame-based simultaneous localization and map construction framework. First, depth and color information are used simultaneously, and the framework may operate on central processing unit (CPU) at high speed based on localization of the key frame, and operate in challenging scene in robust manner. To reduce accumulated errors, the method introduces increment bundle adjustment, which may greatly reduce an operation amount and enable local and global bundle adjustment to be completed in a unified framework. Secondly, provided by the method is a key frame-based fusion method, and a model may be generated online and a three-dimensional model may be updated in real time during adjustment of the key frame's pose.

Abstract: The present disclosure discloses a method for simultaneous localization and mapping, which can reliably handle strong rotation and fast motion. The method provided a simultaneous localization and mapping algorithm framework based on a key frame, which can support rapid local map extension. Under this framework, a new feature tracking method based on multiple homography matrices is provided, and this method is efficient and robust under strong rotation and fast motion. A camera orientation optimization framework based on a sliding window is further provided to increase motion constraint between successive frames with simulated or actual IMU data. Finally, a method for obtaining a real scale of a specific plane and scene is provided in such a manner that a virtual object is placed on a specific plane in real size.

Abstract: A camera pose tracking apparatus may track a camera pose based on frames photographed using at least three cameras, may extract and track at least one first feature in multiple-frames, and may track a pose of each camera in each of the multiple-frames based on first features. When the first features are tracked in the multiple-frames, the camera pose tracking apparatus may track each camera pose in each of at least one single-frame based on at least one second feature of each of the at least one single-frame. Each of the at least one second feature may correspond to one of the at least one first feature, and each of the at least one single-frame may be a previous frame of an initial frame of which the number of tracked second features is less than a threshold, among frames consecutive to multiple-frames.

Abstract: A camera pose tracking apparatus may track a camera pose based on frames photographed using at least three cameras, may extract and track at least one first feature in multiple-frames, and may track a pose of each camera in each of the multiple-frames based on first features. When the first features are tracked in the multiple-frames, the camera pose tracking apparatus may track each camera pose in each of at least one single-frame based on at least one second feature of each of the at least one single-frame. Each of the at least one second feature may correspond to one of the at least one first feature, and each of the at least one single-frame may be a previous frame of an initial frame of which the number of tracked second features is less than a threshold, among frames consecutive to multiple-frames.