An image processing apparatus 1 is provided with: a detecting device 121 that detects, based on a face image 101 in which a face of a human 100 is included, a landmark of the face; a generating device 122 that generates a face angle information 0 that indicates a direction of the face by an angle based on the face image; a correcting device 123 that generates a position information relating to a position of the landmark that is detected by the detecting device and corrects the position information based on the face angle information; and a determining device 124 that determines whether or not an action unit relating to a motion of a facial part that constitutes the face occurs based on the position information that is corrected by the correcting device.

Current inspection processes employed for pipeline networks data acquisition aided with manually locating and recording defects/observations, thus leading labor intensive, prone to error and a time-consuming task thereby resulting in process inefficiencies. Embodiments of the present disclosure provide systems and methods for that leverage artificial intelligence/machine learning models and image processing techniques to automate log and data processing, reports and insights generation thereby reduce dependency on manual analysis, improve annual productivity of survey meterage and bring in process and cost efficiencies into overall asset health management for utilities, thereby enhancing accuracy in defect identification, analysis, classification thereof.

In some embodiments, apparatuses and methods are provided herein useful to detecting and tracking humans. In some embodiments, there is provided a system for detecting and tracking humans from one image to another image including: a camera; a control circuit configure to: receive a first image; detect a plurality of key body joints of a first human captured on the first image; determine segmentations of the plurality of key body joints to determine one or more body parts of the first human; determine a color distribution map of aggregate pixels associated with each body part of the first human on the first image; and cause a database to store the color distribution map; and a database comprising one or more color distribution map sets each associated with a detected human in a captured image of the camera.

An object association method, apparatus and system, and a storage medium are provided. The method includes: obtaining a first image and a second image; and determining an association relationship between objects in the first image and objects in the second image based on surrounding information of the objects in the first image and surrounding information of the objects in the second image, where the surrounding information of one object is determined according to pixels within a set range around a bounding box of the object in the image where the object is located.

An image recognition evaluation program is executed by an evaluation apparatus for evaluating recognition accuracy of an image recognition apparatus performing image segmentation. The evaluation apparatus is caused to perform image processing on an input image to be input to the image recognition apparatus, and generate a plurality of processed input images. Thereafter, the evaluation apparatus is caused to input the generated plurality of processed input images to the image recognition apparatus, and obtain a plurality of output images classified into classes by image segmentation being performed by the image recognition apparatus. Next, the evaluation apparatus is caused to calculate a variance value of each of the plurality of the output images, based on the obtained plurality of output images.

The present application relates to a method and an apparatus for detecting corner points of a lane line, an electronic device and a storage medium. The method comprises: obtaining a road image to be detected; inputting the road image into a pre-trained neural network model to obtain a heat map prediction result, wherein the heat map prediction result comprises a probability of each pixel belonging to a specific corner point category; determining a plurality of different categories of corner points in the road image according to the probability of each pixel belonging to a specific corner point category in the heat map prediction result; and grouping the plurality of different categories of corner points according to a predetermined rule to obtain at least one corner point group. The present application can solve the problem that the corner points of the lane lines cannot be accurately and quickly detected.

Auto-completion of an input partial line pattern. Upon detecting that the user has input the partial line pattern, the scope of the input partial line pattern is matched against corresponding line patterns from a collection of line pattern representations to form a scoped match set of line pattern representations. For one or more of the line pattern representations in the scoped match set, a visualization of completion options is then provided. For example, the corresponding line pattern representation might be displayed in a distinct portion of the display as compared to the input partial line pattern, or perhaps in the same portion in which case, in which case the remaining portion of the line pattern representation might extend off of the input partial line pattern representation.

An edge detecting apparatus according to the present invention includes: a first determining unit configured to determine, based on an input image, at least one of a distance between local maximum pixels which are pixels of which gradation values are local maximum values and a distance between local minimum pixels which are pixels of which gradation values are local minimum values; and a detecting unit configured to detect an edge from the input image with a detection sensitivity based on the distance determined by the first determining unit.

According to the invention, one or more discrete edge binning (“DEB”) features of a DEB template matching system, method and/or computer readable medium may preferably comprise and/or apply an image processing algorithm, preferably for use in template matching. According to the invention, template matching may preferably involve using one or more known reference features to detect and/or localize similar features within an image.

There is provided a framework including systems and methods for analyzing skin parameters from images or videos showing skin. Using a series of Hierarchical Differential Image Filters (HDIF), it becomes possible to detect different skin features such as wrinkles, spots, and roughness. The hierarchical differential image filter computes two enhancements to an image showing skin at two different levels of enhancement, determines a differential image using the two enhancements and computes the skin analysis rating using the differential image. These skin ratings are comparably accurate to actual ratings by dermatologists.