A face identification method includes performing a distance detection to obtain a detected distance value; determining whether the detected distance value is smaller than a distance threshold; when the detected distance value is smaller than the distance threshold, determining a luminance corresponding to the detected distance value and emitting an infrared light according to the luminance; capturing an infrared light image and performing face identification to the infrared light image; and when the face identification is successful, performing a corresponding event. A face identification apparatus configured to perform the face identification method is further provided.

Disclosed are methods, systems, and non-transitory computer-readable medium for color and pattern analysis of images including wearable items. For example, a method may include receiving an image depicting a wearable item, identifying the wearable item within the image by identifying a face of an individual wearing the wearable item or segmenting a foreground silhouette of the wearable item from background image portions of the image, determining a portion of the wearable item identified within the image as being a patch portion representative of the wearable item depicted within the image, deriving one or more patterns of the wearable item based on image analysis of the determined patch portion of the image, deriving one or more colors of the wearable item based on image analysis of the determined patch portion of the image, and transmitting information regarding the derived one or more colors and information regarding the derived one or more patterns.

A method of image processing converts images of different brightness to a common brightness range, the images representing at least partly the same scene. One of images including a local block with movement is selected for forming a composed image from the images. One or more corresponding blocks corresponding to the local block are determined in the images. Each of said one or more corresponding blocks is weighted with at least one of the following: similarity with respect to the local block, a distance from a location of the local block, saturation of the one or more corresponding blocks, and noise of the one or more corresponding blocks. The local block and at least one of the one or more corresponding blocks are combined, or the local block is replaced by at least one of the one or more corresponding blocks based on the weighting for forming the composed image from the images.

Disclosed are methods, systems, and non-transitory computer-readable medium for color and pattern analysis of images including wearable items. For example, a method may include receiving an image depicting a wearable item, identifying the wearable item within the image by identifying a face of an individual wearing the wearable item or segmenting a foreground silhouette of the wearable item from background image portions of the image, determining a portion of the wearable item identified within the image as being a patch portion representative of the wearable item depicted within the image, deriving one or more patterns of the wearable item based on image analysis of the determined patch portion of the image, deriving one or more colors of the wearable item based on image analysis of the determined patch portion of the image, and transmitting information regarding the derived one or more colors and information regarding the derived one or more patterns.

A computing system for decimating video data includes: a processor; a persistent storage system coupled to the processor; and memory storing instructions that, when executed by the processor, cause the processor to decimate a batch of frames of video data by: receiving the batch of frames of video data; mapping, by a feature extractor, the frames of the batch to corresponding feature vectors in a feature space, each of the feature vectors having a lower dimension than a corresponding one of the frames of the batch; selecting a set of dissimilar frames from the plurality of frames of video data based on dissimilarities between corresponding ones of the feature vectors; and storing the selected set of dissimilar frames in the persistent storage system, the size of the selected set of dissimilar frames being smaller than the number of frames in the batch of frames of video data.

A computer transforms high-dimensional data into low-dimensional data. A distance is computed between a selected observation vector and each observation vector of a plurality of observation vectors, a nearest neighbors are selected using the computed distances, and a first sigmoid function is applied to compute a distance similarity value between the selected observation vector and each of the selected nearest neighbors where each of the computed distance similarity values is added to a first matrix. The process is repeated with each observation vector of the plurality of observation vectors as the selected observation vector. An optimization method is executed with an initial matrix, the first matrix, and a gradient of a second sigmoid function that computes a second distance similarity value between the selected observation vector and each of the nearest neighbors to transform each observation vector of the plurality of observation vectors into the low-dimensional space.

In an apparatus for identifying an obstacle around a vehicle, an acquirer is configured to acquire an image captured by a camera mounted to the vehicle. An extractor is configured to extract feature points of the image. A generator is configured to generate an optical flow that is a movement vector from each of the feature points of the image acquired before the current time to a corresponding feature point of the image acquired at the current time. A classifier configured to classify the optical flows into groups each corresponding to an object in the image based on pixel positions of the feature points. An identifier is configured to, for each of the groups that the optical flows are classified by the classifier into, identify whether an object corresponding to the group in the image is a stationary object or a moving object based on a degree of variability in lengths of the optical flows of the group.

Object/facial recognition systems, methods, architectures, mechanisms and/or apparatus for 3D face or object recognition using a 3D surface reconstructed from polarimetric thermal facial/object imager to form a 2D or 3D image which is rotated to conform with a pose of a reference image to allow comparison thereto.

An image processing apparatus includes a setting unit, a detection unit, a matrix calculation unit, a calculation unit, an obtaining unit, a deriving unit, a patch correction unit, and a generation unit. The setting unit sets a target patch in an input image. The detection unit detects a plurality of similar patches in the input image. The matrix calculation unit calculates a covariance matrix representing correlation between pixels based on the plurality of similar patches. The calculation unit calculates eigenvalues and eigenvectors of the covariance matrix. The obtaining unit obtains a noise amount in the input image. The deriving unit derives a correction matrix based on the eigenvalues, the eigenvectors, the noise amount, and the number of similar patches. The patch correction unit corrects values of pixels in the similar patches based on the correction matrix. The generation unit generates an output image by combining the corrected similar patches.

Disclosed are methods, systems, and non-transitory computer-readable medium for color and pattern analysis of images including wearable items. For example, a method may include receiving an image depicting a wearable item, identifying the wearable item within the image by identifying a face of an individual wearing the wearable item or segmenting a foreground silhouette of the wearable item from background image portions of the image, determining a portion of the wearable item identified within the image as being a patch portion representative of the wearable item depicted within the image, deriving one or more patterns of the wearable item based on image analysis of the determined patch portion of the image, deriving one or more colors of the wearable item based on image analysis of the determined patch portion of the image, and transmitting information regarding the derived one or more colors and information regarding the derived one or more patterns.