Shoppertrak Rct Corporation

Sensormatic Electronics Corporation

Zhiqian Wang

William C Kastilahn

Edward A Marcheselli

Gary Dispensa

Thomas D Stemen

Michael J Paolella

Spencer Neilan

Jeffrey R Rendlen

David Patrick McNeill

Jane Farias

Mikhail Zaturenskiy

Rahul Miglani

Anne Marie Stephen

Techniques for evaluating height data are disclosed herein. Height values for a tracked object are obtained over a specified period of time. Clusters including at least one of the height values are generated. The cluster having the largest amount of height values is identified. A height of the tracked object is estimated from the identified cluster.

System and method for detecting, tracking and counting human objects of interest with an improved height calculation

Techniques for distinguishing objects (e.g., an individual or an individual pushing a shopping cart) are disclosed. An object is detected in images of a scene. A height map is generated from the images, and the object is represented as height values in the height map. Based on height properties associated with another object, it is determined whether the other object is associated with the object. If so determined, the objects are classified separately.

Techniques for automatically identifying secondary objects in a stereo-optical counting system

Apparatus and methods for determining information about one or more objects in a 3-dimensional (3D) space are disclosed. One aspect of the method includes defining a virtual ground plane within a monitored 3D space. The virtual ground plane is divided into a plurality of bins. Each bin has corresponding counter value. An object is detected in a respective image captured by each of a plurality of sensors. A respective line segment is selected corresponding to a respective light between each of the plurality of image sensors and the detected object. One or more bins of the virtual ground plane are selected onto which a respective projected line segment of each respective line segment overlap. Each counter value for each of the one or more selected bins is increased. A location of the object is determined based on a bin of the one or more bins having a highest counter value.

System and method for determining information about objects using multiple sensors

Techniques for calibrating a device having a stereoscopic camera are disclosed. According to an embodiment, the device calibrates the stereoscopic camera using a target provided by a mobile device. One or more zones each defining an area in a field of view of the calibrated stereoscopic camera are generated. The one or more zones are refined based on input provided by the mobile device.

Techniques for calibrating a stereoscopic camera in a device

A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of said existing tracks; updating each said existing track; and maintaining a count of said objects of interest in a given time period based upon said existing tracks created or modified during said given time period.

System and process for detecting, tracking and counting human objects of interest

Disclosed herein are systems and methods for calibrating a stereoscopic imaging device. An example implementation includes receiving, at a processor, a plurality of image pairs from the stereoscopic imaging device and calculating, for each image pair in the plurality of image pairs, a respective row delta value indicative of a deviation along a horizontal axis between the first image captured by the first sensor and the second image captured by the second sensor. The implementation further includes determining a median row delta value based on each respective row delta value and subsequently a set of respective disparities in one or more features in the first image and the second image based on the median row delta value. The method further includes calculating a column delta value and calibrating the stereoscopic imaging device using the median row delta value and the column delta value.

Auto-calibration of stereoscopic imaging device

A system is disclosed that includes: at least one image capturing device at the entrance to obtain images; a reader device; and a processor for extracting objects of interest from the images and generating tracks for each object of interest, and for matching objects of interest with objects associated with RFID tags, and for counting the number of objects of interest associated with, and not associated with, particular RFID tags.

Growing community of inventors

Schaumburg, IL, United States of America

Zhiqian Wang