Abstract: Methods and computer-readable media for presenting a user with advertising content, such as an advertisement or coupon, based on the user's responses to one or more questions are provided. A user may view a web page that includes one or more thumbnails, where each thumbnail represents a media, such as a video clip, an audio clip, or an image. Once a user selects a thumbnail, by hovering a cursor over the thumbnail, for example, a question may appear over the thumbnail. The user may respond to the question, and based on the response, may be provided with some form of relevant advertising content. Subsequent questions may be presented to the user if the user selects more than one thumbnail in a session, and thus the user may be provided with highly relevant advertising content that is based on responses to more than one question.

Abstract: Methods and computer storage media for creating contextual-display advertisements are provided. A request for a contextual-display advertisement to be presented on a page is received. Upon receiving the request, the page is evaluated to determine the context of the page so that the resulting advertisement is contextually related to the requesting page. The contextually related text and base image are extracted from their respective database to be merged into a contextual-display advertisement. The visual characteristics of the advertisement text are manipulated to provide visual congruity among the elements of the advertisement. Additionally, the placement of the text on the base image is optimized to provide a contextual-image advertisement that is then rendered to be presented on the requesting page.

Abstract: The present invention provides a computer implemented process for detecting multi-view multi-pose objects. The process comprises training of a classifier for each intra-class exemplar, training of a strong classifier and combining the individual exemplar-based classifiers with a single objective function. This function is optimized using the two nested AdaBoost loops. The first loop is the outer loop that selects discriminative candidate exemplars. The second loop, the inner loop selects the discriminative candidate features on the selected exemplars to compute all weak classifiers for a specific position such as a view/pose. Then all the computed weak classifiers are automatically combined into a final classifier (strong classifier) which is the object to be detected.

Abstract: An electronic device includes a main body and a rotating base. The rotating base has a first vent and is pivoted at the main body and adapted to rotate between an operating position and a retracted position relatively to the main body. When the rotating base is located at the operating position, the first vent is exposed out of the main body, and when the rotating base is located at the retracted position, the first vent is retracted into the main body.

Abstract: A method and apparatus for recognizing an object, comprising providing a set of scene features from a scene, pruning a set of model features, generating a set of hypotheses associated with the pruned set of model features for the set of scene features, pruning the set of hypotheses, and verifying the set of pruned hypotheses is provided.

Abstract: Systems, methods, computer-readable media, and graphical user interfaces for facilitating advertisement placement over video content are provided. Images within a video are partitioned into image regions. Upon partitioning images into image regions, an intrusiveness score is determined for each image region. Based on the intrusiveness scores, optimal placement of an advertisement within the video is determined.

Abstract: The present invention provides a computer implemented process for detecting multi-view multi-pose objects. The process comprises training of a classifier for each intra-class exemplar, training of a strong classifier and combining the individual exemplar-based classifiers with a single objective function. This function is optimized using the two nested AdaBoost loops. The first loop is the outer loop that selects discriminative candidate exemplars. The second loop, the inner loop selects the discriminative candidate features on the selected exemplars to compute all weak classifiers for a specific position such as a view/pose. Then all the computed weak classifiers are automatically combined into a final classifier (strong classifier) which is the object to be detected.

Abstract: The present invention provides a computer implemented process for detecting multi-view multi-pose objects. The process comprises training of a classifier for each intra-class exemplar, training of a strong classifier and combining the individual exemplar-based classifiers with a single objective function. This function is optimized using the two nested AdaBoost loops. The first loop is the outer loop that selects discriminative candidate exemplars. The second loop, the inner loop selects the discriminative candidate features on the selected exemplars to compute all weak classifiers for a specific position such as a view/pose. Then all the computed weak classifiers are automatically combined into a final classifier (strong classifier) which is the object to be detected.

Abstract: A method and apparatus for tracking a movable object using a plurality of images, each of which is separated by an interval of time is disclosed. The plurality of images includes first and second images. The method and apparatus include elements for aligning the first and second images as a function of (i) at least one feature of a first movable object captured in the first image, and (ii) at least one feature of a second movable object captured in the second image; and after aligning the first and second images, comparing at least one portion of the first image with at least one portion of the second image.

Abstract: Computer-readable media and computerized methods for utilizing an awareness of video content within a media file to incorporate an advertisement therein are provided. Building the video-content awareness involves performing an offline authoring process to generate a trajectory. In particular, the offline authoring process includes targeting an object appearing in the video content, tracking movement of the object over a sequence of frames within the media file, and, based on the tracked movement, writing locations of the object to the trajectory. In an online rendering process, invoked upon initiating play of the media file, the advertisement is automatically selected and dynamically placed on top of the video content as a function of the locations within the trajectory. Accordingly, by repositioning the advertisement (typically an animation) within the video content based on the movement of the object, an illusion that the advertisement visually interacts with the object is generated.

Abstract: The present invention provides an improved system and method for object detection with histogram of oriented gradient (HOG) based support vector machine (SVM). Specifically, the system provides a computational framework to stably detect still or not moving objects over a wide range of viewpoints. The framework includes providing a sensor input of images which are received by the “focus of attention” mechanism to identify the regions in the image that potentially contain the target objects. These regions are further computed to generate hypothesized objects, specifically generating selected regions containing the target object hypothesis with respect to their positions. Thereafter, these selected regions are verified by an extended HOG-based SVM classifier to generate the detected objects.

Abstract: Described herein are techniques and components for displaying a text advertisement in an online video being viewed by a user. The advertisement is selected based on keywords associated with the online video or the user, and the selected advertisement is presented as an overlay on the rendered video over regions of frames determined to be less important in the video. To determine importance, every frame of the online video is divided into grids, and parameters of the visual data in each grid are analyzed. Based on the analysis of each grid, regions in successive frames are identified to display the selected advertisement.

Abstract: Methods and computer-readable media for presenting a user with advertising content, such as an advertisement or coupon, based on the user's responses to one or more questions are provided. A user may view a web page that includes one or more thumbnails, where each thumbnail represents a media, such as a video clip, an audio clip, or an image. Once a user selects a thumbnail, by hovering a cursor over the thumbnail, for example, a question may appear over the thumbnail. The user may respond to the question, and based on the response, may be provided with some form of relevant advertising content. Subsequent questions may be presented to the user if the user selects more than one thumbnail in a session, and thus the user may be provided with highly relevant advertising content that is based on responses to more than one question.

Abstract: A method and apparatus for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras is disclosed The method includes collecting at least two pairs of feature maps, where the at least two pairs of feature maps are derived from features of objects captured in the images. The method further includes computing, as a function of at least two pairs of feature maps, at least one first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class.

Abstract: Videos are retargeted to a target display for viewing with little to no geometric distortion or video information loss. Salient regions of video frames may be determined using scale-space spatiotemporal information. Video information loss may be a result of spatial loss, due to cropping, and resolution loss, due to resizing. A desired cropping window may be determined using a coarse-to-fine searching strategy. Video frames may be cropped with a window that matches an aspect ratio of the target display, and resized isotropically to match a size of the target display.

Abstract: Systems, methods, computer-readable media, and graphical user interfaces for facilitating advertisement placement over video content are provided. Images within a video are partitioned into image regions. Upon partitioning images into image regions, an intrusiveness score is determined for each image region. Based on the intrusiveness scores, optimal placement of an advertisement within the video is determined.

Abstract: Methods and computer storage media for creating contextual-display advertisements are provided. A request for a contextual-display advertisement to be presented on a page is received. Upon receiving the request, the page is evaluated to determine the context of the page so that the resulting advertisement is contextually related to the requesting page. The contextually related text and base image are extracted from their respective database to be merged into a contextual-display advertisement. The visual characteristics of the advertisement text are manipulated to provide visual congruity among the elements of the advertisement. Additionally, the placement of the text on the base image is optimized to provide a contextual-image advertisement that is then rendered to be presented on the requesting page.

Abstract: Efficient image display on a display screen (e.g., in terms of number, space, resolution, and/or distortion) is facilitated by implementing one or more specialized select and pack routines for images. That is, representative images are selected from an image database, based on desired resolution and distortion, then resized and packed into a display arrangement that enhances use of display screen space. This allows, for example, images to be sent to a user from an image database more quickly, with more desirable resolution, and less distortion than traditional display techniques.

Abstract: A system and method for identifying objects, particularly vehicles, between two non-overlapping cameras. More specifically, the method and system determines whether a vehicle depicted in an image captured by a first camera is the same vehicle or a different vehicle than a vehicle depicted in an image captured by a second camera. This intra-camera analysis determines whether the vehicle viewed by the first camera is the same as the vehicle viewed by the second camera, without directly matching the two vehicle images, thus eliminating the problems and inaccuracies caused by disparate environmental conditions acting on the two cameras, such as dramatic appearance and aspect changes.

Abstract: An incremental motion estimation system and process for estimating the camera pose parameters associated with each image of a long image sequence. Unlike previous approaches, which rely on point matches across three or more views, the present system and process also includes those points shared only by two views. The problem is formulated as a series of localized bundle adjustments in such a way that the estimated camera motions in the whole sequence are consistent with each other. The result of the inclusion of two-view matching points and the localized bundle adjustment approach is more accurate estimates of the camera pose parameters for each image in the sequence than previous incremental techniques, and providing an accuracy approaching that of global bundle adjustment techniques except with processing times about 100 to 700 times faster than the global approaches.