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Sriram Sethuraman

Researcher at Sarnoff Corporation

Publications -  37
Citations -  1429

Sriram Sethuraman is an academic researcher from Sarnoff Corporation. The author has contributed to research in topics: Motion estimation & Computer science. The author has an hindex of 17, co-authored 29 publications receiving 1405 citations. Previous affiliations of Sriram Sethuraman include Carnegie Mellon University & LG Electronics.

Papers
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Compression and transmission of depth maps for image-based rendering

TL;DR: This work considers applications using depth-based image-based rendering (IBR), where the synthesis of arbitrary views occur at a remote location, necessitating the compression and transmission of depth maps, and considers region-of-interest (ROI) coding, where those regions of the image where accurate depth is most crucial are identified.
Patent

Method and apparatus for encoding video information

TL;DR: In this article, a method and apparatus for encoding, illustratively, a video information stream to produce an encoded information stream according to a group of frames (GOF) information structure where the GOF structure and, optionally, a bit budget are modified in response to, respectively, information discontinuities and the presence of redundant information in the video stream.
Patent

Latency-based statistical multiplexing

TL;DR: In this paper, an off-line profiling tool analyzes typical video applications offline in order to generate profiles of different types of video applications that are then accessed in real-time by a call admission manager responsible to controlling the admission of new video application sessions as well as the assignment of admitted applications to specific available video encoders.
Patent

Method and apparatus for region-based allocation of processing resources and control of input image formation

TL;DR: In this paper, an approach and method for classifying regions of an image, based on the relative importance of the various areas and adaptively use the importance information to allocate processing resources and input image formation is presented.
Patent

Intra-frame quantizer selection for video compression

TL;DR: In this article, the authors propose a method to adjust the quantizer values as needed to meet the frame-level bit allocation, while ensuring spatial and temporal smoothness in frame quality.