Abstract: A method is provided for a user-sensing remote control system including a TV and a remote control. The method includes obtaining sensing data from a plurality of sensors in the remote control related to a user of the remote control, pre-processing the sensing data, and determining a user identity space containing a plurality of possible user identities of the user using a predetermined statistical algorithm. The method also includes determining whether there is a dominant possible user identity; when it is determined that there is no dominant possible user identity, selecting one or more possible user identities from the user identity space and updating the user identity space until there is a dominant possible user identity; and when it is determined that there is a dominant possible user identity, presenting the dominant possible user identity as the identity of the user to other applications.

Abstract: Embodiments of the present invention include systems and methods for processing and coding image data. In one embodiment, image data is coded using a first image coding process. If a bit rate constraint is satisfied, the image data is output. If the bit rate constraint is not satisfied, the image data is coded using a second different coding process. In one embodiment, the second coding process is a layered coding process. In another embodiment, if the constraint is satisfied, quantization data may be included in the output, and may be coded using layered coding. Variable length coding processes and hardware implementations are further disclosed for efficient image processing.

Abstract: The disclosure is directed to techniques for automatic segmentation of a region-of-interest (ROI) video object from a video sequence. ROI object segmentation enables selected ROI or “foreground” objects of a video sequence that may be of interest to a viewer to be extracted from non-ROI or “background” areas of the video sequence. Examples of a ROI object are a human face or a head and shoulder area of a human body. The disclosed techniques include a hybrid technique that combines ROI feature detection, region segmentation, and background subtraction. In this way, the disclosed techniques may provide accurate foreground object generation and low-complexity extraction of the foreground object from the video sequence. A ROI object segmentation system may implement the techniques described herein. In addition, ROI object segmentation may be useful in a wide range of multimedia applications that utilize video sequences, such as video telephony applications and video surveillance applications.

Abstract: A method for an intelligent user-interaction control system includes generating a plurality of summary video frames for a certain time of incoming bit-stream of a video program to be shown on a display, and detecting a hold command from a user to stop the video program. The method also includes presenting the plurality of summary video frames to the user on the display after stopping the video program, obtaining a user selection on a selected summary frame from the plurality of the summary video frames, presenting a plurality of objects of interest from the selected summary frame to the user on the display, and determining a user-selected object of interest from the plurality of objects of interest. The method also includes searching the selected object in an online database to obtain searching results corresponding to the selected object, and prompting the user about the searching results.

Abstract: A stereo 3D video frame includes left and right components that are combined to produce a stereo image. For a given amount of distortion, the left and right components may have different impacts on perceptual visual quality of the stereo image due to asymmetry in the distortion response of the human eye. A 3D video encoder adjusts an allocation of coding bits between left and right components of the 3D video based on a frame-level bit budget and a weighting between the left and right components. The video encoder may generate the bit allocation in the rho (?) domain. The weighted bit allocation may be derived based on a quality metric that indicates overall quality produced by the left and right components. The weighted bit allocation compensates for the asymmetric distortion response to reduce overall perceptual distortion in the stereo image and thereby enhance or maintain visual quality.

Abstract: Embodiments of the present invention provide methods and associated architecture of accuracy adaptive and scalable vector graphics rendering including rendering a graphic comprising a plurality of line segments by processing each of the plurality of line segments in a first pass, and processing each of a plurality of pixels through which the plurality of line segments pass in a second pass, automatically detecting one or more rendering errors of the graphic, and correcting the one or more rendering errors. Other embodiments may be described and/or claimed.

Abstract: A method and apparatus for generating stereoscopic images of a scene is described. The apparatus may have a first image sensor, a second image sensor spaced apart from the first image sensor, a diversity combine module to combine image data from the first and second image sensors, and an image processing module configured to process combined image data from the diversity combine module may be used to generate stereoscopic images of a scene.

Abstract: Methods, software, and apparatuses for graphics processing, including caching pixel data of one or more tiles of a graphics surface. Methods generally include setting a caching bit corresponding to the surface, setting tile pattern bits corresponding to tiles in the surface, and when the caching bit is active, storing one or more pixel values in a cache memory. When at least one tile contains pixels having the same value for at least one predetermined parameter, the caching bit and the corresponding tile pattern bits may be active. Apparatuses generally include a pixel memory, a cache memory, and a controller including logic configured to reserve the caching bit, tile pattern bits, and same pixel values in cache memory when the caching bit is active.

Abstract: A system for minimizing interactions with at least an input mechanism, comprising at least a management server communicatively coupled to at least a user endpoint device, the user endpoint device comprising at least a display, an input mechanism, and a transponder mechanism configured to communicate data related to interactions with the input mechanism and displayed content, at least one storage device configured to store data based on content displayed on the display, interactions with the input mechanism, and content available for viewing, and at least one processor configured to use software to process the data such that a configuration of content data is prepared for display and the configuration is derived from at least the interactions with the input mechanism and the configuration is designed to minimize additional user interactions with the input mechanism to select the prepared content data.

Abstract: This disclosure describes rate control techniques that can improve video coding based on a “two-pass” approach. The first pass codes a video sequence using a first set of quantization parameters (QPs) for the purpose of estimating rate-distortion characteristics of the video sequence based on the statistic of the first pass. A second set of QPs can then be defined for a second coding pass. The estimated rate-distortion characteristics of the first pass are used to select Qps for the second pass in a manner that minimizes quality fluctuation between the frames of the video sequence. Furthermore, selection of the second set of QPs may also substantially maximize quality of the frames at the substantially minimized quality flucuation in order to achieve low average frame distortion with the minimized quality fluctuation.

Abstract: Embodiments of the present invention include systems and methods for processing and coding image data. In one embodiment, image data is coded using a first image coding process. If a bit rate constraint is satisfied, the image data is output. If the bit rate constraint is not satisfied, the image data is coded using a second different coding process. In one embodiment, the second coding process is a layered coding process. In another embodiment, if the constraint is satisfied, quantization data may be included in the output, and may be coded using layered coding. Variable length coding processes and hardware implementations are further disclosed for efficient image processing.

Abstract: Methods and systems for using a video data compression algorithm with parallel processing capability are provided. AC and DC coefficients associated with blocks of the video data, along with quantization errors, may be encoded using a variable length code. The quantization errors may be encoded using a scheme that assigns priorities to the quantization errors based on the position of their associated AC and/or DC coefficients in a block of the video data. The quantization errors may be appended to a bitstream in an order based on these priorities that enables parallel coding of the quantization errors and AC and DC coefficients in each block of video data. Data packing schemes may also be applied to the coded data to maximize the use of bandwidth resources in encoding and/or decoding.

Abstract: Techniques for complexity-adaptive and automatic two-dimensional (2D) to three-dimensional (3D) image and video conversion which classifies a frame of a 2D input into one of a flat image class and a non-flat image class are described. The flat image class frame is directly converted into 3D stereo for display. The frame that is classified as a non-flat image class is further processed automatically and adaptively, based on complexity, to create a depth map estimate. Thereafter, the non-flat image class frame is converted into a 3D stereo image using the depth map estimate or an adjusted depth map. The adjusted depth map is processed based on the complexity.

Abstract: The disclosure is directed to decoder-side region-of-interest (ROI) video processing. A video decoder determines whether ROI assistance information is available. If not, the decoder defaults to decoder-side ROI processing. The decoder-side ROI processing may estimate the reliability of ROI extraction in the bitstream domain. If ROI reliability is favorable, the decoder applies bitstream domain ROI extraction. If ROI reliability is unfavorable, the decoder applies pixel domain ROI extraction. The decoder may apply different ROI extraction processes for intra-coded (I) and inter-coded (P or B) data. The decoder may use color-based ROI generation for intra-coded data, and coded block pattern (CBP)-based ROI generation for inter-coded data. ROI refinement may involve shape-based refinement for intra-coded data, and motion- and color-based refinement for inter-coded data.

Abstract: A method for personalized video depth adjustment includes receiving a video frame, obtaining a frame depth map based on the video frame, and determining content genre of the video frame by classifying content of the video frame into one or more categories. The method also includes identifying a user viewing the video frame, retrieving depth preference information for the user from a user database, and deriving depth adjustment parameters based on the content genre and the depth preference information for the user. The method further includes adjusting the frame depth map based on the depth adjustment parameters, and providing a 3D video frame for display at a real-time playback rate on a user device of the user. The 3D video frame is generated based on the adjusted frame depth map.

Abstract: The disclosure is directed to techniques for automatic segmentation of a region-of-interest (ROI) video object from a video sequence. ROI object segmentation enables selected ROI or “foreground” objects of a video sequence that may be of interest to a viewer to be extracted from non-ROI or “background” areas of the video sequence. Examples of a ROI object are a human face or a head and shoulder area of a human body. The disclosed techniques include a hybrid technique that combines ROI feature detection, region segmentation, and background subtraction. In this way, the disclosed techniques may provide accurate foreground object generation and low-complexity extraction of the foreground object from the video sequence. A ROI object segmentation system may implement the techniques described herein. In addition, ROI object segmentation may be useful in a wide range of multimedia applications that utilize video sequences, such as video telephony applications and video surveillance applications.

Abstract: The disclosure is directed to techniques for automatic segmentation of a region-of-interest (ROI) video object from a video sequence. ROI object segmentation enables selected ROI or “foreground” objects of a video sequence that may be of interest to a viewer to be extracted from non-ROI or “background” areas of the video sequence. Examples of a ROI object are a human face or a head and shoulder area of a human body. The disclosed techniques include a hybrid technique that combines ROI feature detection, region segmentation, and background subtraction. In this way, the disclosed techniques may provide accurate foreground object generation and low-complexity extraction of the foreground object from the video sequence. A ROI object segmentation system may implement the techniques described herein. In addition, ROI object segmentation may be useful in a wide range of multimedia applications that utilize video sequences, such as video telephony applications and video surveillance applications.

Abstract: The disclosure is directed to decoder-side region-of-interest (ROI) video processing. A video decoder determines whether ROI assistance information is available. If not, the decoder defaults to decoder-side ROI processing. The decoder-side ROI processing may estimate the reliability of ROI extraction in the bitstream domain. If ROI reliability is favorable, the decoder applies bitstream domain ROI extraction. If ROI reliability is unfavorable, the decoder applies pixel domain ROI extraction. The decoder may apply different ROI extraction processes for intra-coded (I) and inter-coded (P or B) data. The decoder may use color-based ROI generation for intra-coded data, and coded block pattern (CBP)-based ROI generation for inter-coded data. ROI refinement may involve shape-based refinement for intra-coded data, and motion- and color-based refinement for inter-coded data.

Abstract: The disclosure is directed to techniques for automatic segmentation of a region-of-interest (ROI) video object from a video sequence. ROI object segmentation enables selected ROI or “foreground” objects of a video sequence that may be of interest to a viewer to be extracted from non-ROI or “background” areas of the video sequence. Examples of a ROI object are a human face or a head and shoulder area of a human body. The disclosed techniques include a hybrid technique that combines ROI feature detection, region segmentation, and background subtraction. In this way, the disclosed techniques may provide accurate foreground object generation and low-complexity extraction of the foreground object from the video sequence. A ROI object segmentation system may implement the techniques described herein. In addition, ROI object segmentation may be useful in a wide range of multimedia applications that utilize video sequences, such as video telephony applications and video surveillance applications.

Abstract: The disclosure is directed to techniques for region-of-interest (ROI) video processing based on low-complexity automatic ROI detection within video frames of video sequences. The low-complexity automatic ROI detection may be based on characteristics of video sensors within video communication devices. In other cases, the low-complexity automatic ROI detection may be based on motion information for a video frame and a different video frame of the video sequence. The disclosed techniques include a video processing technique capable of tuning and enhancing video sensor calibration, camera processing, ROI detection, and ROI video processing within a video communication device based on characteristics of a specific video sensor. The disclosed techniques also include a sensor-based ROI detection technique that uses video sensor statistics and camera processing side-information to improve ROI detection accuracy.