Lenel Systems International, Inc.

Arie Pikaz

Oren Golan

Jeffrey Sanders Raj

Sharon Pikaz, Legal Representative

A system for counting objects, such as people, crossing an area includes a camera configured for capturing video images along a surface in the area. The surface includes a plurality of detectable features on the surface. A user interface allows an individual to define a region where object detection is desired. A processor processes the images and counts a detected object in the region when criteria for counting are satisfied.

System and method for counting people near external windowed doors

A system for counting objects, such as people, is provided having a camera () for capturing video images along an image plane () in which two-dimensional shapes or design () are spaced along the image plane (), and a computer system () for receiving the images and detecting objects associated with change occurring in the images, and counting one of the detected objects when of the detected objects approximates a shape () associated with the object being counted (e.g., ellipse shape, to count a person) that fully or substantially blocks a portion said two-dimensional shapes or design () in the image associated with the detected object, and the detected object meeting other criteria for the object, such as size or compactness of detected change within the object. The system is especially useful for counting people near external windowed doors () of a building entranceway doors by discriminating between spurious light crossing the image plane and people.

A system having a camera () for capturing video images of a scene in successive image frames, and a computer system (or) for receiving such video images. The computer system periodically generates a background image of the scene from multiple successive image frames () and extracts features in the background image (), and extracts features for each new image frame received from the camera (). For each new image frames, the new image frame and the last periodically generated background image are correlated at common locations (parts or regions) associated with the features extracted from the last periodically generated background image and features of the new image frame (), to determine non-correlated features in the new image frame with respect to the last periodically generated background image (). If the number and/or percentage of non-correlated features are sufficiently high, and/or the spatial distribution of non-correlated features is sufficiently low, the image frame is determined to have an invalid background (). When multiple successive frames are determined as having invalid backgrounds, the camera () represents an invalid camera.

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Givatayim, Israel

Arie Pikaz