A flow meter includes an image sensor and a processor. The image sensor is configured to capture an image of a drip chamber. The processor is configured to determine whether the captured image of the drip chamber contains a match to a template, and to apply a blurring function to the image captured by the image sensor of the drip chamber such that the processor can determine if the captured image contains a match to the template.

Systems and methods according to one or more embodiments are provided for detecting an object in a field of view of an imaging device. An object may be detected by an imaging device when the object is present along a trajectory in a target scene. In one example, a system includes a memory component to store a plurality of images of the target scene and a processor. The processor is configured to define the trajectory between two locations within the target scene and extract a subset of pixel values from each of successive images corresponding to the trajectory. The extracted subsets of pixel values are processed to detect an object within the target scene. Additional systems and methods are also provided.

An apparatus configured for head-worn by a user, includes: a screen configured to present graphics for the user; a camera system configured to view an environment in which the user is located; and a processing unit coupled to the camera system, the processing unit configured to: obtain a first image with a first resolution, the first image having a first corner, determine a second image with a second resolution, the second image having a second corner that corresponds with the first corner in the first image, wherein the second image is based on the first image, the second resolution being less than the first resolution, detect the second corner in the second image, determine a position of the second corner in the second image, and determine a position of the first corner in the first image based at least in part on the determined position of the second corner in the second image.

Systems and methods for assessing text legibility in an electronic document are disclosed. According to certain aspects, the electronic document may include a text layer and a background layer, and an electronic device may generate a text mask comprising a set of glyphs at certain positions. The electronic device may analyze the text mask to generate an output comprising a set of bounding boxes that indicate legibility degrees of the respective glyphs included in the text mask. The electronic device may display the output for review and assessment by a user, who may use the electronic device to facilitate any modifications to the electronic document.

Evaluating structural changes in a sample resulting from a treatment of the sample. At least one sample of the material is scanned before and after the treatment and a first and a second image of the sample are obtained. The first and the second images are registered in a full spatial resolution using at least one region of the first image and at least one region of the second image, the regions corresponding to the same part of the sample. The registered images are analyzed and the changes in each sample caused by the performed treatment are evaluated.

A system and method are provided for capturing an image with correct skin tone exposure. In use, one or more faces are detected having threshold skin tone within a scene. Next, based on the detected one or more faces, the scene is segmented into one or more face regions and one or more non-face regions. A model of the one or more faces is constructed based on a depth map and a texture map, the depth map including spatial data of the one or more faces, and the texture map includes surface characteristics of the one or more faces. The one or more images of the scene are captured based on the model. Further, in response to the capture, the one or more face regions are processed to generate a final image.

A system for frame rate conversion of a video that includes the use of key points.

An electronic device and method for human skin detection based on a human body-prior is provided. A color image of a person is acquired, and a 3D body model of the person is estimated based on the color image. One or more unclothed parts of the 3D body model are identified. The one or more unclothed parts correspond to one or more body parts, of which at least a portion of skin remains uncovered by clothes. From the color image, pixel information corresponding to the one or more unclothed parts is extracted and classification information is determined based on the pixel information. The classification information includes a set of values, each indicating a likelihood of whether a corresponding pixel of the color image is part of an unclothed skin portion of the person. The unclothed skin portion is detected in the color image based on the classification information.

A system, method, and computer program product for providing a lasso selection tool for a stereoscopic image is disclosed. The method includes the steps of obtaining a lasso region of a stereoscopic image pair based on a path defined by a user using a lasso selection tool. An object in a first image of the stereoscopic image pair is identified, where the object is at least partially included within the lasso region and the object is identified in a second image of the stereoscopic image pair.

A method for use with a computing device. The method may include receiving a data set including a plurality of univariate data points and determining a target kernel bandwidth for a kernel density estimator (KDE). Determining the target kernel bandwidth may include computing a plurality of sample KDEs and selecting the target kernel bandwidth based on the sample KDEs. The method may further include computing the KDE for the data set using the target kernel bandwidth. For one or more tail regions of the data set, the method may further include computing one or more respective tail extensions. The method may further include computing and outputting a renormalized piecewise density estimator that, in each tail region, equals a renormalization of the respective tail extension for that tail region, and, outside the one or more tail regions, equals a renormalization of the KDE.