A system is provided for object localization in image data. The system includes an object localization framework comprising a plurality of object localization processes. The system is configured to receive an image comprising unannotated image data having at least one object in the image, access a first object localization process of the plurality of object localization processes, determine first bounding box information for the image using the first object localization process, wherein the first bounding box information comprises at least one first bounding box annotating at least a first portion of the at least one object in the image, and receive first feedback regarding the first bounding box information determined by the first object localization process. The system is further configured to persist the image with the first bounding box information or access a second object localization process based on the first feedback.

The present application relates to an image processing method and system. The method includes: determining an enhanced image of a target object of an input image based on a segmentation algorithm, where the enhanced image of the target object comprises an image in which each pixel classified as the target object is displayed in an enhanced manner; and determining a positioning image of the target object by applying an integral image algorithm to the enhanced image of the target object.

Example systems and methods to transform events and/or mood associated with playing media into lighting effects are disclosed herein. An example apparatus includes a content identifier to identify a first event occurring during presentation of media content at a first time. The example apparatus includes a content driven analyzer to determine a first lighting effect to be produced by a light-producing device based on the first event and instruct the light-producing device to produce the first lighting effect based on the first event during presentation of the media content. The content identifier is to identify a second media event occurring during presentation of the media content at a second time after the first time. The content driven analyzer is to instruct the light-producing device to one of maintain the first lighting effect based on the second event or produce a second lighting effect based on the second event during presentation of the media content.

In a state where a tracking flag is on, a search controller determines, with respect to a previous frame, whether an amount of change in positional coordinates of a feature point of a face in the current frame is within a predetermined range, whether an amount of change in face orientation is within a predetermined angle range, and whether an amount of change in sight line direction is within a predetermined range. When the conditions are satisfied in all these determinations, the change in the detection result in the current frame with respect to the previous frame is considered as being within an allowable range, and continuously in a subsequent frame, detection processing for a face image is performed in accordance with a face image area saved in a tracking information storage unit.

Disclosed is face tracking method and device. The method includes: acquiring an initial facial image in a to-be-tracked picture; performing binarization processing on the initial facial image according to a standard range of color parameter and an actual value of the color parameter of each pixel in the initial facial image, to obtain a binarized facial image; acquiring a position of a preset organ in the binarized facial image; and acquiring a position of a final facial image according to the position of the preset organ and a position of the initial facial image.

Aspects of the present disclosure provide an image-based face detection and recognition system that processes and/or analyzes portions of an image using image strips and cascading classifiers to detect faces and/or various facial features, such an eye, nose, mouth, cheekbone, jaw line, etc.

Machine vision methods and systems determine if an object within a work field has one or more predetermined features. Methods comprise capturing image data of the work field, applying a filter to the image data, in which the filter comprises an aspect corresponding to a specific feature, and based at least in part on the applying, determining if the object has the specific feature. Systems comprise a camera system configured to capture image data of the work field, and a controller communicatively coupled to the camera system and comprising non-transitory computer readable media having computer-readable instructions that, when executed, cause the controller to apply a filter to the image data, and based at least in part on applying the filter, determine if the object has the specific feature. Robotic installation methods and systems that utilize machine vision methods and systems also are disclosed.

An apparatus comprises a sensor (102) comprising a left camera (102a) and a right camera (102b). A processor (104) is coupled to the sensor. The processor is configured to produce an image and disparity data for the image, and search for a vertical object (122a, 122b) within the image using the disparity data. The processor is also configured to determine whether the vertical object is a bale of material using the image, and compute an orientation of the bale relative to the sensor using the disparity data. The sensor and processor can be mounted for use on an autonomous bale mover comprising an integral power system, a ground-drive system, a bale loading system, and a bale carrying system.

An intelligent face recognition system for an installed security system can include a camera and a local or remote video processor including a face recognition engine. The video processor can be configured to receive the image information from the one or more cameras, and generate an alert for communication to a user device based on a recognition event in the environment. In an example, the face recognition engine is configured to apply machine learning to analyze images from the camera and determine whether the images include or correspond to an enrolled face, and the face recognition engine is configured to provide the recognition event based on the determination.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for facial recognition using fractal features are disclosed. In one aspect, a method includes the actions of accessing data encoding a facial image, the facial image including a face. The actions further include generating a hierarchical graphical model of the face in the facial image, the hierarchical graphical model including more than nodes from at least one level, each level approximating the face within a contour. The actions further include applying a bank of filters to the face at a particular node, each filter spanning more than one scale and at least one direction. The actions further include analyzing filter responses from the bank of filters applied at each direction to obtain a similarity measure that consolidates filter responses from filters applied at more than one scale. The actions further include generating a vector representation.