Avigilon Analytics Corporation

Videoiq, Inc.

Motorola Solutions, Inc.

The Mathworks, Inc.

Irobot Corporation

Avo USA Holding 2 Corporation

Avigilon Patent Holding 2 Corporation

Dimitri A Lisin

Mahesh Saptharishi

Aleksey Lipchin

Igor Reyzin

Adel Fakih

Yao Chen

A mobile cleaning robot configured to clean an environment. The mobile cleaning robot can include a body and a drivetrain operable to move the body within the environment. The robot can include a sensor connected to the body and configured to generate a sensor signal based on interactions between the mobile cleaning robot and the environment. The robot can include an image capture device connected to the body and configured to generate an image stream based on an optical field of view of the image capture device. The robot can include a controller connected to the body and configured to determine whether the mobile cleaning robot is in a stasis condition based on the image stream and the sensor signal. The controller can also update a map of the environment based on the stasis determination.

Mapping stasis for mobile cleaning robot

A camera system comprises an image capturing device, object detection module, object tracking module, and match classifier. The object detection module receives image data and detects objects appearing in one or more of the images. The object tracking module temporally associates instances of detected objects, each of which has a signature representing features of the detected object. The match classifier matches object instances by analyzing data derived from the signatures. The match classifier determines whether the signatures match.

Method of searching data to identify images of an object captured by a camera system

A camera system comprises an image capturing device, and connected to it are an object classification module and a calibration module. The object classification module is operable to determine whether or not an object in an image is a member of an object class, and the calibration module is operable to estimate representative sizes of the object. The object classification module may determine a confidence parameter that is used by the calibration module, or conversely, the calibration module may produce a size that is used by the classification module.

Video object classification with object size calibration

A camera system comprises an image capturing device and an object classification module connected to the image capturing device. The object classification module is operable to determine whether or not an object in an image is a member of an object class. The object classification module includes multiple decision steps configured in a cascade configuration, wherein at least one of the multiple decision steps is operable to (a) accept an object as a member of the object class, (b) reject an object as a member of the object class, and (c) call on a next step to determine whether or not an object is a member of the object class.

Cascading video object classification

A device is configured to receive an image including a calibration pattern and apply a filter to the image based on a first coordinate plane. The device is configured to determine a first set of response peaks associated with the calibration pattern based on applying the filter, the first set of response peaks being associated with a set of control points and a set of boundary points. The device is configured to determine a second set of response peaks associated with the calibration pattern based on a second coordinate plane and a third coordinate plane, the second set of response peaks being associated with the boundary points. The device is configured to determine the control points based on determining the first set of response peaks and the second set of response peaks, and provide information that identifies the control points.

Detecting control points for camera calibration

A camera system comprises an image capturing device, object detection module, object tracking module, and match classifier. The object detection module receives image data and detects objects appearing in one or more of the images. The object tracking module temporally associates instances of a first object detected in a first group of the images. The first object has a first signature representing features of the first object. The match classifier matches object instances by analyzing data derived from the first signature of the first object and a second signature of a second object detected in a second image. The second signature represents features of the second object derived from the second image. The match classifier determine whether the second signature matches the first signature. A training process automatically configures the match classifier using a set of possible object features.

Method of generating index elements of objects in images captured by a camera system

A camera system comprises an image capturing device and an object classification module connected to the image capturing device. The image capturing device has a field of view and produces image data representing an image of the field of view. The object classification module is operable to determine whether an object in an image is a member of an object class. The object classification module includes N decision steps configured in a cascade configuration, wherein at least one of the N decision steps is operable to (a) accept an object as a member of the object class, (b) reject an object as a member of the object class, and (c) call on a next step to determine whether an object is a member of the object class.

Growing community of inventors

Shrewsbury, MA, United States of America

Dimitri A Lisin