Christopher J Hillar

US Patent:

20020046245, Apr 18, 2002

Filed:

Aug 15, 2001

Appl. No.:

09/930695

Inventors:

Christopher Hillar - Houston TX, US
Christopher Priebe - Houston TX, US

International Classification:

G06F015/16

US Classification:

709/205000, 345/788000

Abstract:

A computer-implemented system for creating web pages of complex design that are viewable via a network. The system employs a web authoring software module that is platform-independent and can be accessed by clients to create customized web pages. A client can select the size and location of information elements to be placed on the web page without complex programming or the use of templates. The system also supports the use and editing of multiple information elements, such as images, of various formats.

US Patent:

20210112256, Apr 15, 2021

Filed:

Oct 14, 2019

Appl. No.:

16/601419

Inventors:

- San Francisco CA, US
Darren Rhea - Austin TX, US
Christopher Hillar - San Francisco CA, US
Alexander Terekhov - San Francisco CA, US
Felix Effenberger - Stuttgart, DE

International Classification:

H04N 19/167
H04N 19/154
G06K 9/00
H04N 19/176
G06N 3/08

Abstract:

Semantically-segmented video compression includes loading a frame of video imagery, determining a context for the frame, selecting an object of interest for the context and identifying within the frame, a portion of the frame of the imagery deemed to be of greater interest than other portions of the frame of video imagery based upon the object of interest of the context determined for the video imagery, and an object, that has been pre-specified to be of importance to the context. A hybrid compression of the video imagery is then performed that includes both a higher quality compression of the portion of the video imagery determined to be a region of higher interest that produces a minimization of loss during decompression and also a compression of the other portions of the video imagery determined not to be a region of higher interest that produces more loss during decompression.

US Patent:

20170249536, Aug 31, 2017

Filed:

Feb 29, 2016

Appl. No.:

15/056528

Inventors:

Christopher J. Hillar - San Francisco CA, US
Kilian Koepsell - San Francisco CA, US
Ram Mehta - Brooklyn NY, US

International Classification:

G06K 9/66
H04N 19/426
G06K 9/62

Abstract:

An invention based on learning a discrete recurrent neural network for a given signal domain is described. In one implementation to the domain of visual images, the method can be used to efficiently compress digital photographs and to devise a new perceptual distortion measure between images that well-matches data collected from a human psychophysics experiment. Other applications of the invention include unsupervised detection of recurrent patterns in high-dimensional data and Shannon-optimal error-correcting coding from few training examples.