Chi Ling Li

US Patent:

20180129865, May 10, 2018

Filed:

Sep 20, 2017

Appl. No.:

15/709897

Inventors:

- Princeton NJ, US
Quoc-Huy Tran - Santa Clara CA, US
Xiang Yu - Mountain View CA, US
Manmohan Chandraker - Santa Clara CA, US
Chi Li - San Jose CA, US

International Classification:

G06K 9/00
G06T 15/10
G06N 3/02

Abstract:

An action recognition system and method are provided. The action recognition system includes an image capture device configured to capture an actual image depicting an object. The action recognition system includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN thereto to generate an image pair including a 2D and 3D geometric structure of the object. The processor is configured to control a device to perform a response action in response to an identification of an action performed by the object, wherein the identification of the action is based on the image pair.

US Patent:

20180129910, May 10, 2018

Filed:

Sep 20, 2017

Appl. No.:

15/709748

Inventors:

- Princeton NJ, US
Quoc-Huy Tran - Santa Clara CA, US
Xiang Yu - Mountain View CA, US
Manmohan Chandraker - Santa Clara CA, US
Chi Li - San Jose CA, US

International Classification:

G06K 9/62
G06T 15/40
G06K 9/00
G06N 3/02
G06F 17/50

Abstract:

A system and method are provided. The system includes an image capture device configured to capture an actual image depicting an object. The system also includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, a set of synthetic images with corresponding intermediate shape concept labels. The processor is also configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is further configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D geometric structure and a 3D geometric structure of the object depicted in the actual image.

US Patent:

20180130229, May 10, 2018

Filed:

Sep 20, 2017

Appl. No.:

15/709849

Inventors:

- Princeton NJ, US
Quoc-Huy Tran - Santa Clara CA, US
Xiang Yu - Mountain View CA, US
Manmohan Chandraker - Santa Clara CA, US
Chi Li - San Jose CA, US

International Classification:

G06T 7/73
G06N 3/08

Abstract:

A surveillance system and method are provided. The surveillance system includes an image capture device configured to capture an actual image of a target area depicting an object. The surveillance system further includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, synthetic images with intermediate shape corresponding concept labels. The processor is further configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to generate an image pair including a 2D and 3D geometric structure of the object depicted in the actual image. The surveillance system further includes a display device configured to display the image pair.

US Patent:

20180130355, May 10, 2018

Filed:

Sep 20, 2017

Appl. No.:

15/709814

Inventors:

- Princeton NJ, US
Quoc-Huy Tran - Santa Clara CA, US
Xiang Yu - Mountain View CA, US
Manmohan Chandraker - Santa Clara CA, US
Chi Li - San Jose CA, US

International Classification:

G08G 1/16
G06K 9/00
G05D 1/02

Abstract:

A system and method are provided for driving assistance. The system includes an image capture device configured to capture an actual image relative to an outward view from a motor vehicle and depicting an object. The system further includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is further configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D and 3D geometric structure of the object. The processor is additionally configured to perform an action to mitigate a likelihood of harm involving the motor vehicle, based on the image pair.