Microsoft Technology Licensing, LLC

Yan-Feng Sun

Lei Zhang

Wei-Ying Ma

Mingjing Li

Hong-Jiang Zhang

Lie Lu

Xian-Sheng Hua

Yong Rui

Tao Mei

Rong Xiao

Yuxiao Hu

Imran Aziz

Chun-Che Wu

Mingju Zhang

Chi Pong Timothy Leung

Techniques and constructs to facilitate suggestion of image-based search queries can provide personalized trending image search queries. The constructs may enable identification of trending image searches and further personalize those trending image search queries for an identified user based on information about on the user's search history and the search histories of other users. The constructs also may select a representative image for display to the user, such that selection of the representative image will execute the search query. The representative image may be selected from a plurality of candidate images based on its burstiness.

Personalized trending image search suggestion

Embodiments of the present invention relate to aggregating product information from a variety of sources to generate user interfaces that allow users to navigate and discover products. Product information is aggregated from both feed and crawl sources, and product entities are identified within the aggregate product information. In some embodiments, product entities are associated with product classes, and product class detail pages are generated that include product entities within each product class and allow users to view correlations between those produce entities. In some embodiments, relationships are identified between product entities. When a user selects to view information for a given product entity, information is provided indicating similar product entities that have a relationship with the given product entity.

Navigating product relationships within a search system

A method and system for detecting faces at different views within images that allocates the computational effort based on a prior probability associated with a view is provided. A face detection system determines whether an image contains a face using detectors that are adapted to detect faces at various views and a filter that filters out windows of the image that are provided to a detector based on a prior probability associated with the view of the detector. Each view has an associated prior probability that a face from a collection of real-life home photographs will be at that view. The face detection system allocates increasing computational effort to a detector as the prior probability of its view increases.

Accelerated face detection based on prior probability of a view

A method and system for cropping an image is provided. The cropping system automatically crops an image by selecting an image template whose condition is best satisfied by the image and then by selecting a cropping of the image that best attains the goal of the selected image template. The cropping system may use a metric or objective function to rate how well a cropping attains the goal of the selected image template. The cropping system may apply various optimization algorithms to identify a cropping that is the best as indicated by the metric. The cropping system can then automatically crop the image based on the identified cropping.

Automatically cropping an image

Systems, engines, user interfaces, and methods allow a user to select a group of images, such as digital photographs, and assign to the group of images the name of a person who is represented in each of the images. The name is automatically propagated to the face of the person, each time the person's face occurs in an image. In one implementation, names and associations are shared between a browsing mode for viewing multiple images at once and a viewer mode, for viewing one image at a time. The browsing mode can provide a menu of candidate names for annotating a face in a single image of the viewer mode. Likewise, the viewer mode can provide annotated face information to the browser mode for facilitating name propagation. Identification of a person's face in multiple images can be accomplished not only by finding similarities in facial features but also by finding similarities in contextual features near the face in different images.

Efficient propagation for face annotation

A 'music video parser' automatically detects and segments music videos in a combined audio-video media stream. Automatic detection and segmentation is achieved by integrating shot boundary detection, video text detection and audio analysis to automatically detect temporal boundaries of each music video in the media stream. In one embodiment, song identification information, such as, for example, a song name, artist name, album name, etc., is automatically extracted from the media stream using video optical character recognition (OCR). This information is then used in alternate embodiments for cataloging, indexing and selecting particular music videos, and in maintaining statistics such as the times particular music videos were played, and the number of times each music video was played.

Automatic detection and segmentation of music videos in an audio/video stream

Systems and methods for indexing and retrieving images are described herein. The systems and methods analyze an image to determine its texture moments. The pixels of the image are converted to gray scale. Textural attributes of the pixels are determined. The textural attributes are associated with the local texture of the pixels and are derived from coefficients of Discrete Fourier Transform associated with the pixels. Statistical values associated with the textural attributes of the pixels are calculated. The texture moments of the image are determined from the statistical value.

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Beijing, China

Yan-Feng Sun