Computation cost associated with emerging video coding standards, such as H.264, can be overcome by changing the coding algorithm so that compressed bitstreams incur fewer operations. This technology may increase the performances of devices requiring good quality video output with less power consumption in signal processing. This technology describes an algorithm that optimizes selection of motion vectors and motion compensation block modes to significantly reduce computational cost while keeping video quality unchanged. Time-based encoding and decoding of digital video streams is optimized and results in low power requirements for converting large analog signals to smaller digital formats for processing, transfer, and storage. This technology improves transmission of encoded video over wireless networks by improving over simple bit reduction as it incorporates real time updates of the wireless network performance with real-time error resilience processing to maximize video quality. This invention also allows delivery of 3D video, where 3D images are generated from 2D images using a multiple-viewpoint scheme. Multiple perspectives of the same scene are delivered to the viewer at the same time.
Typically, encoded video streams are transmitted to a decoder through a wireless network where a video transcoder determines the bit error rate of wireless network and the modifying spatial and temporal resilience in the encoded video stream. The encoded video bit stream is then re-encoded at a predetermined bit rate incorporating the resilience modification. However, conventional schemes use channel coding which rely on techniques such as forward error correction (FEC) are not always decodable at the point of delivery. The transcoder described in this technology uses source-coding methods to add spatial and temporal resilience to the transmitted code, and employs rate distortion theory to compress the signal. The transcoder decides on the amount of resilience to add and compression ratio based on a specific network's bandwidth and bit error rate (the quantitative measure of how lossy the network is). As such it optimizes the re-encoding of the signal to most effectively and efficiently meet the task at hand.
3D video is created from 2D using a coding scheme that computes multiple viewpoint images at any one instant in time. Image views from multiple angles are computed using a combination of perspective projection of 3D models, 3D texture mapping, and image warping. All aspects of this technology have been validated through numerical studies, simulations, and demonstrations.
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