Abstract: A method performed by an electronic device is described. The method includes determining a haziness confidence level based on multiple modalities. The method also includes determining whether to perform an action based on the haziness confidence level. The method may include performing the action, including performing haziness reduction based on the haziness confidence level.

Abstract: A method for identifying assets is provided. The method includes illuminating an identification pattern associated with the asset with non-visible light. The identification pattern includes retroreflective material that represents identity information of the asset. The method further includes adjusting either a shutter speed of an image sensor, or a power of the non-visible light, or both, based on motion state of the asset. The image sensor is configured to receive response of the retroreflective material to the non-visible light. Furthermore, the method includes the step of identifying the asset based on decoded identity information. The decoded identity information is obtained by processing the response of the retroreflective material.

Abstract: A method includes selecting at least two objects within a primary video stream, generating a first video stream from the primary video stream that includes a first of the selected objects, and generating a second video stream from the primary video stream that includes a second of the selected objects. The primary video stream has a primary field of view, and the first and second video streams have respective first and second fields of view that are more narrow than the primary field of view. The first field of view includes a portion of the primary field of view that is not within the second field of view, and the second field of view includes a portion of the primary field of view that is not within the first field of view.

Abstract: A method of generating metadata includes using at least one digital image to select a plurality of objects, wherein the at least one digital image depicts the plurality of objects in relation to a physical space. The method also includes, by at least one processor and based on information indicating positions of the selected objects in a location space, producing metadata that identifies one among a plurality of candidate geometrical arrangements of the selected objects.

Abstract: A method of image retrieval includes obtaining information identifying a plurality of selected objects and selecting one among a plurality of candidate geometrical arrangements. This method also includes, by at least one processor, and in response to the selecting, identifying at least one digital image, among a plurality of digital images, that depicts the plurality of selected objects arranged according to the selected candidate geometrical arrangement.

Abstract: A method includes receiving information that identifies a reference position in a location space. The method also includes receiving data that identifies one among a plurality of candidate geometrical arrangements. The method also includes producing a representation that depicts a plurality of objects which are arranged, relative to the reference position in the location space, according to the identified candidate geometrical arrangement.

Abstract: A method includes receiving first data defining a first bounding box for a first image of a sequence of images. The first bounding box corresponds to a region of interest including a tracked object. The method also includes receiving object tracking data for a second image of the sequence of images, the object tracking data defining a second bounding box. The second bounding box corresponds to the region of interest including the tracked object in the second image. The method further includes determining a similarity metric for first pixels within the first bounding box and search pixels within each of multiple search bounding boxes. Search coordinates of each of the search bounding boxes correspond to second coordinates of the second bounding box shifted in one or more directions. The method also includes determining a modified second bounding box based on the similarity metric.

Abstract: A method of generating metadata includes using at least one digital image to select at least one among a plurality of objects, wherein the at least one digital image depicts the plurality of objects in relation to a physical space. The method also includes, in response to the selecting at least one object, determining a position of the at least one object in a location space. The method also includes, based on said determined position, producing metadata that identifies one among a plurality of separate regions that divide the location space, wherein said plurality of separate regions includes regions of unequal size.

Abstract: Systems, devices and methods for improved tracking with an electronic device are disclosed. The disclosures employ advanced exposure compensation and/or stabilization techniques. The tracking features may therefore be used in an electronic device to improve tracking performance under dramatically changing lighting conditions and/or when exposed to destabilizing influences, such as jitter. Historical data related to the lighting conditions and/or to the movement of a region of interest containing the tracked object are advantageously employed to improve the tracking system under such conditions.

Abstract: A method for detecting and tracking a target includes detecting the target using a plurality of feature cues, fusing the plurality of feature cues to form a set of target hypotheses, tracking the target based on the set of target hypotheses and a scene context analysis, and updating the tracking of the target based on a target motion model.

Abstract: A method for detecting and tracking a target object is described. The method includes performing motion-based tracking for a current video frame by comparing a previous video frame and the current video frame. The method also includes selectively performing object detection in the current video frame based on a tracked parameter.

Abstract: A method for identifying assets is provided. The method includes illuminating an identification pattern associated with the asset with non-visible light. The identification pattern includes retroreflective material that represents identity information of the asset. The method further includes adjusting either a shutter speed of an image sensor, or a power of the non-visible light, or both, based on motion state of the asset. The image sensor is configured to receive response of the retroreflective material to the non-visible light. Furthermore, the method includes the step of identifying the asset based on decoded identity information. The decoded identity information is obtained by processing the response of the retroreflective material.

Abstract: In accordance with one aspect of the present technique, a method includes receiving one or more videos from one or more image capture devices. The method further includes generating a video-loop of the person from the one or more videos. The video-loop depicts the person in the commercial site. The method also includes generating an action clip from the video-loop. The action clip includes a suspicious action performed by the person in the commercial site. The method further includes generating an activity summary of the person including the video-loop and the action clip.

Abstract: A method for detecting and tracking a target includes detecting the target using a plurality of feature cues, fusing the plurality of feature cues to form a set of target hypotheses, tracking the target based on the set of target hypotheses and a scene context analysis, and updating the tracking of the target based on a target motion model.

Abstract: Systems provided herein include a learning environment and an agent. The learning environment includes an avatar and an object. A state signal corresponding to a state of the learning environment includes a location and orientation of the avatar and the object. The agent is adapted to receive the state signal, to issue an action capable of generating at least one change in the state of the learning environment, to produce a set of observations relevant to a task, to hypothesize a set of action models configured to explain the observations, and to vet the set of action models to identify a learned model for the task.

Abstract: An advertising system is disclosed. In one embodiment, the system includes a processor and a memory including application instructions for execution by the processor. The application instructions may include a visual analytics engine to analyze visual information including human activity and a content engine separate from the visual analytics engine to provide advertising content to one or more potential customers. Further, the instructions may include an interface module to enable information generated from analysis of the human activity by the visual analytics engine to be transferred to the content engine in accordance with a specification in which the information generated is characterized with a hierarchical, object-oriented data structure. Additional methods, systems, and articles of manufacture are also disclosed.

Abstract: A tracking and recognition system is provided. The system includes a computer vision-based identity recognition system configured to recognize one or more persons, without a priori knowledge of the respective persons, via an online discriminative learning of appearance signature models of the respective persons. The computer vision-based identity recognition system includes a memory physically encoding one or more routines, which when executed, cause the performance of constructing pairwise constraints between the unlabeled tracking samples. The computer vision-based identity recognition system also includes a processor configured to receive unlabeled tracking samples collected from one or more person trackers and to execute the routines stored in the memory via one or more algorithms to construct the pairwise constraints between the unlabeled tracking samples.

Abstract: An advertising system is disclosed. In one embodiment, the system includes an advertising display configured to provide an advertisement to potential customers and a camera configured to capture images of the potential customers when the potential customers pass the advertising display. The system may also include an image processing system having a processor and a memory. The memory may include application instructions for execution by the processor, and the image processing system may be configured to execute the application instructions to derive usage characteristics of the potential customers with respect to the advertising display through analysis of the captured images. Additional methods, systems, and articles of manufacture are also disclosed.

Abstract: Image quality is assessed for a digital image that is a composite of tiles or other image segments, especially focus accuracy for a microscopic pathology sample. An algorithm or combination of algorithms correlated to image quality is applied to pixel data at margins where adjacent image segments overlap and thus contain the same content in separately acquired images. The margins may be edges merged to join the image segments smoothly into a composite image, and typically occur on four sides of the image segments. The two versions of the same image content at each margin are processed by the quality algorithm, producing two assessment values. A sign and difference value are compared with other image segments, including by subsets selected for the orientation of the margins on sides on the image segments. The differences are mapped to displays. Selection criteria determine segments to be re-acquired.

Abstract: The system and method disclosed herein provides an integrated and automated workflow, sensor, and reasoning system that automatically detects breaches in protocols, appropriately alarms and records these breaches, facilitates staff adoption of protocol adherence, and ultimately enables the study of protocols for care comparative effectiveness. The system provides real-time alerts to medical personnel in the actual processes of care, thereby reducing the number of negative patient events and ultimately improving staff behavior with respect to protocol adherence.