Sri International

Raia Hadsell

Rakesh Kumar

Supun Samarasekera

Harpreet Singh Sawhney

Bogdan C Matei

Ryan Villamil

Ajay Divakaran

Mayank Bansal

Han-Pang Chiu

Taragay Oskiper

Zhiwei Zhu

Bogdan Calin Mihai Matei

Sang-Hack Jung

Jayan Eledath

Lu Wang

A multi-sensor, multi-modal data collection, analysis, recognition, and visualization platform can be embodied in a navigation capable vehicle. The platform provides an automated tool that can integrate multi-modal sensor data including two-dimensional image data, three-dimensional image data, and motion, location, or orientation data, and create a visual representation of the integrated sensor data, in a live operational environment. An illustrative platform architecture incorporates modular domain-specific business analytics 'plug ins' to provide real-time annotation of the visual representation with domain-specific markups.

Real-time system for multi-modal 3D geospatial mapping, object recognition, scene annotation and analytics

A method and apparatus for providing three-dimensional navigation for a node comprising an inertial measurement unit for providing gyroscope, acceleration and velocity information (collectively IMU information); a ranging unit for providing distance information relative to at least one reference node; at least one visual sensor for providing images of an environment surrounding the node; a preprocessor, coupled to the inertial measurement unit, the ranging unit and the plurality of visual sensors, for generating error states for the IMU information, the distance information and the images; and an error-state predictive filter, coupled to the preprocessor, for processing the error states to produce a three-dimensional pose of the node.

Method and apparatus for generating three-dimensional pose using multi-modal sensor fusion

A computer implemented method for detecting the presence of one or more pedestrians in the vicinity of the vehicle is disclosed. Imagery of a scene is received from at least one image capturing device. A depth map is derived from the imagery. A plurality of pedestrian candidate regions of interest (ROIs) is detected from the depth map by matching each of the plurality of ROIs with a 3D human shape model. At least a portion of the candidate ROIs is classified by employing a cascade of classifiers tuned for a plurality of depth bands and trained on a filtered representation of data within the portion of candidate ROIs to determine whether at least one pedestrian is proximal to the vehicle.

Method and apparatus for real-time pedestrian detection for urban driving

A computer implemented method for unattended detection of a current terrain to be traversed by a mobile device is disclosed. Visual input of the current terrain is received for a plurality of positions. Audio input corresponding to the current terrain is received for the plurality of positions. The video input is fused with the audio input using a classifier. The type of the current terrain is classified with the classifier. The classifier may also be employed to predict the type of terrain proximal to the current terrain. The classifier is constructed using an expectation-maximization (EM) method.

Audio based robot control and navigation

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Princeton Junction, NJ, United States of America

Raia Hadsell