A probe pose is detected in fluoroscopy medical imaging. The pose of the probe through a sequence of fluoroscopic images is detected. The detection relies on an inference framework for visual tracking overtime. By applying visual tracking, the pose through the sequence is consistent or the pose at one time guides the detection of the probe at another time. Single frame drop-out of detection may be avoided. Verification using detection of the tip of the probe and/or weighting of possible detections by separate detection of markers on the probe may further improve the accuracy.

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.

Aspects of the disclosure relate to a dynamic distance estimation output platform that utilizes improved computer vision and perspective transformation techniques to determine vehicle proximities from video footage. A computing platform may receive, from a visible light camera located in a first vehicle, a video output showing a second vehicle that is in front of the first vehicle. The computing platform may determine a longitudinal distance between the first vehicle and the second vehicle by determining an orthogonal distance between a center-of-projection corresponding to the visible light camera, and an intersection of a backside plane of the second vehicle and ground below the second vehicle. The computing platform may send, to an autonomous vehicle control system, a distance estimation output corresponding to the longitudinal distance, which may cause the autonomous vehicle control system to perform vehicle control actions.

The disclosure provides a method for calculating a passenger crowdedness degree, comprising: establishing a video data collection environment and starting collecting video data of passengers getting on and off; reading the collected video data of passengers getting on and off and pre-processing a plurality of successive image frames of the video data; identifying a human head according to the pre-processing result and taking the detected human head as a target object to be tracked by mean-shift; and judging the behaviors of getting on and off of a passenger in the area where the target object is positioned and determining the crowdedness degree of passengers inside a vehicle according to the numbers of the passengers getting on and off. The disclosure also provides a system for calculating a passenger crowdedness degree. The disclosure can effectively reduce the false detection, leak detection and error detection of the head top.

The present invention provides a method for tracking face in a video, comprising steps of taking an image sample from a video; extracting and storing a target face feature according to the image sample; dividing the video into one or more scene; and labeling one or more face matching the target face feature. Accordingly, an actor's facial expression and motion can be extracted with ease and used as training materials or subject matters for discussion.

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.

A system for predicting occurrence of a defective image includes: an input device configured to input image data into an image forming apparatus; and a hardware processor configured to analyze a spatial frequency of gradient distribution of an image in accordance with a size of a density irregularity specific to the image forming apparatus with respect to the input image data and to calculate a probability of a conspicuous density irregularity of the size in regard to the image formed by the image forming apparatus based on the image data with reference to an index of correlation between an analysis result and an evaluation value of the density irregularity.

A self-determining inspection method for automated optical wire bond inspection comprising obtaining an image of a semiconductor component comprising wire bonds; detecting a plurality of wire bonds on the semiconductor component image; detecting a wire between at least two of the plurality of detected wire bonds; determining an inspection region of interest corresponding to at least one detected wire bond and at least one detected wire; and inspecting the detected wire bond along the region of interest.

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.

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.