Sri International

Ishani Chakraborty

Hui Ting Cheng

Omar Javed

Harpreet Singh Sawhney

Ajay Divakaran

Elizabeth E Shriberg

Steven S Weiner

Jingen Liu

Behjat Siddiquie

David Chisolm

A computing system for recognizing salient events depicted in a video utilizes learning algorithms to detect audio and visual features of the video. The computing system identifies one or more salient events depicted in the video based on the audio and visual features.

Recognizing salient video events through learning-based multimodal analysis of visual features and audio-based analytics

An entity interaction recognition system algorithmically recognizes a variety of different types of entity interactions that may be captured in two-dimensional images. In some embodiments, the system estimates the three-dimensional spatial configuration or arrangement of entities depicted in the image. In some embodiments, the system applies a proxemics-based analysis to determine an interaction type. In some embodiments, the system infers, from a characteristic of an entity detected in an image, an area or entity of interest in the image.

Recognizing entity interactions in visual media

A unified framework detects and classifies people interactions in unconstrained user generated images. Previous approaches directly map people/face locations in two-dimensional image space into features for classification. Among other things, the disclosed framework estimates a camera viewpoint and people positions in 3D space and then extracts spatial configuration features from explicit three-dimensional people positions.

3D visual proxemics: recognizing human interactions in 3D from a single image

Growing community of inventors

Franklin Park, NJ, United States of America

Ishani Chakraborty