Mitsubishi Electric Research Laboratories, Inc.

Massachusetts Institute of Technology

Mitsubishi Denki Kabushiki Kaisha

Mitsubishi Electric Corporation

Emin Martinian

Anthony Vetro

Jun Xin

Huifang Sun

Jonathan S Yedidia

Alexander Behrens

Sehoon Yea

Ali Azarbayejani

Gregory W Wornell

Ying-zong Huang

Stark C Draper

Ram Zamir

Ashish Khisti

Jong Dae Oh

Serdar Ince

Sergey M Yekhanin

Akhish Khisti

Multiview videos are acquired of a scene with corresponding cameras arranged at poses, such that there is view overlap between any pair of cameras. V-frames are generated from the multiview videos. The V-frames are encoded using only spatial prediction. Then, the V-frames are inserted periodically in an encoded bit stream to provide random temporal access to the multiview videos. Additional view dependency information enables the decoding of a reduced number of frames prior to accessing randomly a target frame for a specified view and time, and decoding the target frame. The method also decodes multiview videos by maintaining a reference picture list for a current frame of a plurality of multiview videos, and predicting each current frame of the plurality of multiview videos according to reference pictures indexed by the associated reference picture list.

Method and system for decoding multiview videos with prediction dependencies

A method randomly accesses multiview videos. Multiview videos are acquired of a scene with corresponding cameras arranged at poses, such that there is view overlap between any pair of cameras. V-frames are generated from the multiview videos. The V-frames are encoded using only spatial prediction. Then, the V-frames are inserted periodically in an encoded bit stream to provide random temporal access to the multiview videos. Additional view dependency information enables the decoding of a reduced number of frames prior to accessing randomly a target frame for a specified view and time, and decoding the target frame.

Method and system for randomly accessing multiview videos with known prediction dependency

Biometric parameters acquired from human forces, voices, fingerprints, and irises are used for user authentication and access control. Because the biometric parameters are continuous and vary from one reading to the next, syndrome codes are applied to determine biometric syndrome vectors. The biometric syndrome vectors can be stored securely while tolerating an inherent variability of biometric data. The stored biometric syndrome vector is decoded during user authentication using biometric parameters acquired at that time. The syndrome codes can also be used to encrypt and decrypt data.

Biometric based user authentication and data encryption

A method processes a multiview videos of a scene, in which each video is acquired by a corresponding camera arranged at a particular pose, and in which a view of each camera overlaps with the view of at least one other camera. Side information for synthesizing a particular view of the multiview video is obtained in either an encoder or decoder. A synthesized multiview video is synthesized from the of multiview videos and the side information. A reference picture list is maintained for each current frame of each of the multiview videos, the reference picture indexes temporal reference pictures and spatial reference pictures of the acquired multiview videos and the synthesized reference pictures of the synthesized multiview video. Each current frame of the multiview videos is predicted according to reference pictures indexed by the associated reference picture list.

Method and system for processing multiview videos for view synthesis using side information

A system and method synthesizes multiview videos. Multiview videos are acquired of a scene with corresponding cameras arranged at a poses such that there is view overlap between any pair of cameras. A synthesized multiview video is generated from the acquired multiview videos for a virtual camera. A reference picture list is maintained for each current frame of each of the multiview videos and the synthesized video. The reference picture list indexes temporal reference pictures and spatial reference pictures of the acquired multiview videos and the synthesized reference pictures of the synthesized multiview video. Then, each current frame of the multiview videos is predicted according to reference pictures indexed by the associated reference picture list during encoding and decoding.

Method and system for synthesizing multiview videos

A method randomly accesses multiview videos. Multiview videos are acquired of a scene with corresponding cameras arranged at poses, such that there is view overlap between any pair of cameras. V-frames are generated from the multiview videos. The V-frames are encoded using only spatial prediction. Then, the V-frames are inserted periodically in an encoded bitstream to provide random temporal access to the multiview videos.

Method for randomly accessing multiview videos

First biometric parameters are acquired from a user. Input data are encrypted according to the biometric parameters to produce ciphertext. The biometric parameters are encoded using a syndrome encoder to produce a syndrome code. The ciphertext and the syndrome code are associated with each other and stored in a computer readable media so that only the same user can subsequently decrypt the cipher text.

A system and method manages multiview videos. A reference picture list is maintained for each current frame of multiple multiview videos. The reference picture list indexes temporal reference pictures, spatial reference pictures and synthesized reference pictures of the multiview videos. Then, each current frame of the multiview videos is predicted according to reference pictures indexed by the associated reference picture list during encoding and decoding.

Method and system for managing reference pictures in multiview videos

A method decomposes multiview video acquired of a scene by multiple cameras. Each multiview video includes a sequence of frames, and each camera provides a different view of the scene. A prediction mode is selected from a temporal prediction mode, a spatial prediction mode, and a view interpolation prediction mode. The multiview videos are then decomposed into low band frames, high band frames, and side information according to the selected prediction mode.

Multiview video decomposition and encoding

A method converts an input image of noisy wrapped phases to an output image of absolute unwrapped phases. The noisy wrapped phases in the input image are represented as a set of re-wrapped phases and a set of phase shifts. The set of re-wrapped phases are partitioned into a first group and a second group. Integer differences between the phase shifts are optimized while holding the re-wrapped phases fixed. Then, the first group of re-wrapped phases are optimized, while holding the integer differences between the phase shifts, and the second group of re-wrapped phases fixed. The integer differences between the phase shifts are optimized again, while holding the re-wrapped phases fixed. Then, the second group of re-wrapped phases are optimized, while holding the integer differences between the phase shifts, and the first group of re-wrapped phases fixed. The optimizing steps are repeated until the re-wrapped phase converge. Then, the converged re-wrapped phases and integer differences between the phase shifts are output as an output image of absolute unwrapped phases.

Method and system for determining unwrapped phases from noisy two-dimensional wrapped-phase images

Described are techniques for performing lossy encoding. Source data and quality data are received by an encoder. The encoder maps the source data into a compressed representation having a level of distortion in accordance with the quality information. The compressed representation may be decoded without using the quality information.

Lossy data compression exploiting distortion side information

A method quantizes an input signal of N samples into a string of k symbols drawn from a q-ary alphabet. A complementary method reproduces a minimally distorted version of the input signal from the quantized string, given some distortion measure. First, an &lsqb;N,k&rsqb; linear error-correcting code that has a sparse generator factor graph representation is selected. A fixed mapping from q-ary symbols to samples is selected. A soft-input decoder and an encoder for the SGFG codes is selected. A cost function is determined from the input signal and a distortion measure, using the fixed mapping. The decoder determines an information block corresponding to a code word of the SGFG code with a low cost for the input signal. The input signal can be reproduced using the encoder for the SGFG code, in combination with the fixed mapping.

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Arlington, MA, United States of America

Emin Martinian