Toyota Motor Engineering & Manufacturing North America, Inc.

Intelligent Fusion Technology, Inc.

Haibin Ling

Danil V Prokhorov

Genshe Chen

Xue Mei

Erik Philip Blasch

Khanh D Pham

Dan Shen

Bin Jia

Sixiao Wei

Kui Liu

Carolyn Sheaff

Yi Wu

Described herein are systems and methods for multimodal recurrent network processing. In an embodiment, a system for evaluating multimodal data comprising a multimodal data input and a multimodal processing module is described. The multimodal data input may comprise the multimodal data, the multimodal data may comprise a first modality and a second modality. The multimodal processing module may be configured to receive the multimodal data comprising the first modality and the second modality; evaluate the first modality using a first recursive neural network comprising a first transformation matrix; evaluate the second modality using a second recursive neural network comprising the first transformation matrix; and determine an output based, at least in part, on evaluating the first modality and the second modality.

RGB-D scene labeling with multimodal recurrent neural networks

In accordance with various embodiments of the disclosed subject matter, a method and a system for detecting multiple objects from real-time images are provided. The method comprises: performing, using a CPU host, an image segmentation process to divide real-time input images into a plurality of image partitions; performing, by multiple GPUs, a fast block-wise registration process, a mark setting process, a background generation process, a foreground generation process based on a Hyper-Q computation infrastructure, and a support vector machine classification process; and generating, by the CPU host, visualization classification images.

Method and system for detecting multiple moving objects from real-time aerial images

Methods and devices for demonstrating three-player pursuit-evasion (PE) game are provided using a hardware-in-loop test-bed. Robots including pursuer robots and an evader robot are arranged on a solid surface. A drone is positioned flying above to oversee the robots to capture a video or an image sequence of the robots. A robot thread process and a drone thread process are implemented by a computer. In the robot thread process, a tracking-by-detection process is perform to provide a state of the robot including a location and a heading direction of the robot; a delay compensation is conducted; and a PE game is called to calculate a robot command. In the drone thread process, a drone control is calculated to make the drone follow an evader robot, the drone control is sent to the drone, and user commands are also checked.

Methods and devices for demonstrating three-player pursuit-evasion game

A method and apparatus for tracking an object across a plurality of sequential images, where certain of the images contain motion blur. A plurality of normal templates of a clear target object image and a plurality of blur templates of the target object are generated. In the next subsequent image frame, a plurality of bounding boxes are generated of potential object tracking positions about the target object location in the preceding image frame. For each bounding box image frame, a reconstruction error is generated that one bounding box has a maximum probability that it is the object tracking result in the subsequent image frame.

Blur object tracker using group lasso method and apparatus

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Cherry Hill, NJ, United States of America

Haibin Ling