Abstract: This disclosure discloses an optical sensing device. The device includes a carrier body; a first light-emitting device disposed on the carrier body; and a light-receiving device including a group III-V semiconductor material disposed on the carrier body, including a light-receiving surface having an area, wherein the light-receiving device is capable of receiving a first received wavelength having a largest external quantum efficiency so the ratio of the largest external quantum efficiency to the area is ?13.

Abstract: A framework for a few-shot learning method is disclosed. In a first part, self-supervision and classification supervision are used to train a feature extractor. An example self-supervision method comprises running grayscale images through an edge filter, normalizing the filtered images, setting the normalized images to ground truth, generating feature-extracted images, using a decoder to reconstruct images from the feature-extracted images, determining a loss between the reconstructed images and the ground truth images, and using the loss to update parameters of the feature extractor. In a second part, a few-shot adaptation process is performed to adapt the model to a novel rapid test kit.

Abstract: An image processing system may receive image data from a camera of a user device and perform gaze prediction processing of the image data to predict one or more gaze patterns. The gaze prediction processing may include processing the image data using a neural network to detect faces and/or objects and generate an image feature map. The gaze prediction processing may include performing gaze direction prediction operations using the feature map and detected faces and/or objects to determine gaze direction probability data. The gaze prediction processing may include predicting a gaze pattern based on the gaze direction probability data and the image feature map. The gaze pattern may be short-term (e.g., atomic-level) or long-term (e.g., event-level).

Abstract: A system for aggregation and organization of multimedia data acquired from a plurality of sources can include a data collection element, a multimedia segmentation element, a memory, an extraction element, and a user interface. The data collection element can be configured to receive multimedia data. The multimedia segmentation element can be coupled to the data collection element and can be configured to separate the multimedia data into a plurality of multimedia data segments. The memory can be configured to store hierarchical category information having a plurality of categories. The extraction element can be coupled to the multimedia segmentation element and the memory and can be configured to associate at least one of the plurality of categories with each of the plurality of multimedia data segments.

Abstract: A system for aggregation and organization of multimedia data acquired from a plurality of sources can include a data collection element, a multimedia segmentation element, a memory, an extraction element, and a user interface. The data collection element can be configured to receive multimedia data. The multimedia segmentation element can be coupled to the data collection element and can be configured to separate the multimedia data into a plurality of multimedia data segments. The memory can be configured to store hierarchical category information having a plurality of categories. The extraction element can be coupled to the multimedia segmentation element and the memory and can be configured to associate at least one of the plurality of categories with each of the plurality of multimedia data segments.

Abstract: A system for aggregation and organization of multimedia data acquired from a plurality of sources can include a data collection element, a multimedia segmentation element, a memory, an extraction element, and a user interface. The data collection element can be configured to receive multimedia data. The multimedia segmentation element can be coupled to the data collection element and can be configured to separate the multimedia data into a plurality of multimedia data segments. The memory can be configured to store hierarchical category information having a plurality of categories. The extraction element can be coupled to the multimedia segmentation element and the memory and can be configured to associate at least one of the plurality of categories with each of the plurality of multimedia data segments.

Abstract: Human visual perception is able to recognize a wide range of targets but has limited throughput. Machine vision can process images at a high speed but suffers from inadequate recognition accuracy of general target classes. Systems and methods are provided that combine the strengths of both systems and improve upon existing multimedia processing systems and methods to provide enhanced multimedia labeling, categorization, searching, and navigation.

Abstract: Method for determining one or more viewer affects evoked from visual content using visual sentiment analysis using a correlation model including a plurality of publisher affect concepts correlated with a plurality of viewer affect concepts includes detecting one or more of the plurality of publisher affect concepts present in selected visual content, and determining, using the correlation model, one or more of the plurality of viewer affect concepts corresponding to the one or more of the detected publisher affect concepts. A method for determining one or more visual content to evoke one or more viewer affects using visual sentiment analysis is also provided.

Abstract: The invention provides a system and method for integrating multimedia descriptions in a way that allows humans, software components or devices to easily identify, represent, manage, retrieve, and categorize the multimedia content. In this manner, a user who may be interested in locating a specific piece of multimedia content from a database, Internet, or broadcast media, for example, may search for and find the multimedia content. In this regard, the invention provides a system and method that receives multimedia content and separates the multimedia content into separate components which are assigned to multimedia categories, such as image, video, audio, synthetic and text. Within each of the multimedia categories, the multimedia content is classified and descriptions of the multimedia content are generated. The descriptions are then formatted, integrated, using a multimedia integration description scheme, and the multimedia integration description is generated for the multimedia content.

Abstract: A system for aggregation and organization of multimedia data acquired from a plurality of sources can include a data collection element, a multimedia segmentation element, a memory, an extraction element, and a user interface. The data collection element can be configured to receive multimedia data. The multimedia segmentation element can be coupled to the data collection element and can be configured to separate the multimedia data into a plurality of multimedia data segments. The memory can be configured to store hierarchical category information having a plurality of categories. The extraction element can be coupled to the multimedia segmentation element and the memory and can be configured to associate at least one of the plurality of categories with each of the plurality of multimedia data segments.

Abstract: A system and method is provided for editing and parsing compressed digital information. The compressed digital information may include visual information which is edited and parsed in the compressed domain. In a preferred embodiment, the present invention provides a method for detecting moving objects in a compressed digital bitstream which represents a sequence of fields or frames of video information for one or more captured scenes of video.

Abstract: The invention provides a system and method for integrating multimedia descriptions in a way that allows humans, software components or devices to easily identify, represent, manage, retrieve, and categorize the multimedia content. In this manner, a user who may be interested in locating a specific piece of multimedia content from a database, Internet, or broadcast media, for example, may search for and find the multimedia content. In this regard, the invention provides a system and method that receives multimedia content and separates the multimedia content into separate components which are assigned to multimedia categories, such as image, video, audio, synthetic and text. Within each of the multimedia categories, the multimedia content is classified and descriptions of the multimedia content are generated. The descriptions are then formatted, integrated, using a multimedia integration description scheme, and the multimedia integration description is generated for the multimedia content.

Abstract: The invention provides a system and method for integrating multimedia descriptions in a way that allows humans, software components or devices to easily identify, represent, manage, retrieve, and categorize the multimedia content. In this manner, a user who may be interested in locating a specific piece of multimedia content from a database, Internet, or broadcast media, for example, may search for and find the multimedia content. In this regard, the invention provides a system and method that receives multimedia content and separates the multimedia content into separate components which are assigned to multimedia categories, such as image, video, audio, synthetic and text. Within each of the multimedia categories, the multimedia content is classified and descriptions of the multimedia content are generated. The descriptions are then formatted, integrated, using a multimedia integration description scheme, and the multimedia integration description is generated for the multimedia content.

Abstract: The present invention relates to systems and methods for motion estimation and mode decision for low-complexity H.264 standard decoders. The present invention includes a method for optimizing the selection of motion vectors and motion compensation block modules in a video encoder in order to decrease the complexity of the video upon decoding. The novel method of the present invention may include novel steps for selecting motion vectors, block modes, and for applying a complexity-control algorithm to encode the received input video data sequence in accordance with the identified target complexity level. The present invention may be implemented in accordance with current and future video decoding standards to optimize decoding by reducing decoding complexity and thereby reducing required resources and power consumption.

Abstract: The present invention relates to systems and methods for motion estimation and mode decision for low-complexity H.264 standard decoders. The present invention includes a method for optimizing the selection of motion vectors and motion compensation block modules in a video encoder in order to decrease the complexity of the video upon decoding. The novel method of the present invention may include novel steps for selecting motion vectors, block modes, and for applying a complexity-control algorithm to encode the received input video data sequence in accordance with the identified target complexity level. The present invention may be implemented in accordance with current and future video decoding standards to optimize decoding by reducing decoding complexity and thereby reducing required resources and power consumption.

Abstract: Determining ranked candidate media in response to media query data corresponding to a query media includes receiving the media query data including feature data of the query media, coordinate data, and boundary data, matching the features with corresponding features of an media database using the feature data to identify features in the media database within a predetermined hamming distance in a hash table from the corresponding features of the query media to obtain matched features in the media database, determining candidate media whose number of matched features exceeds a matched feature threshold, generating a geometry similarity score between the query media and each candidate media using the feature data and the coordinate data, generating a boundary similarity score between the query media and each candidate media using the boundary data, ranking the candidate media based on the numbers of matched features, the geometry similarity scores and the boundary similarity scores.

Abstract: Systems and methods are described for determining manipulation history among a plurality of images. The described techniques include selecting a pair of images from the plurality of images, detecting one or more manipulations operable to transform one of the images to the other, and based on the manipulations detected, determining a parent-child relationship between the pair or pairs of images. The described techniques can further include repeating the selecting two images, detecting manipulations, and determining the parent-child relationship for each pairs of images in the plurality of images, constructing a visual migration map for the images, and presenting the visual migration map in a user readable format.

Abstract: Systems and methods for automatically determining an improved view for a visual query in a mobile location or object search are provided. In some embodiments, methods for automatically determining an improved view for a visual query in a mobile location or object search system include obtaining at least one data set based on a prior visual query, wherein the at least one data set includes at least a top location or object and one or more other locations or objects; retrieving at least one distinctiveness measurement for one or more locations or objects in the at least one data set; and determining the improved view based on the retrieved at least one distinctiveness measurement.

Abstract: Human visual perception is able to recognize a wide range of targets but has limited throughput. Machine vision can process images at a high speed but suffers from inadequate recognition accuracy of general target classes. Systems and methods are provided that combine the strengths of both systems and improve upon existing multimedia processing systems and methods to provide enhanced multimedia labeling, categorization, searching, and navigation.

Abstract: Human visual perception is able to recognize a wide range of targets but has limited throughput. Machine vision can process images at a high speed but suffers from inadequate recognition accuracy of general target classes. Systems and methods are provided that combine the strengths of both systems and improve upon existing multimedia processing systems and methods to provide enhanced multimedia labeling, categorization, searching, and navigation.