An image analysis method is applied to estimating a mounting position of a camera and includes utilizing the camera to capture an image toward a target region. The image includes at least one object of interest. The object of interest has a pixel height in the image. The image analysis method further includes obtaining an inclining angle and a rolling angle of the camera relative to the target region, calculating a mounting height of the camera relative to the target region according to an input height and the pixel height of the object of interest, an image capturing parameter of the camera, the inclining angle and the rolling angle, and performing video content analysis on the image according to the image capturing parameter, the inclining angle, the rolling angle and the mounting height of the camera.

Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

A method and system are described. The method includes capturing a set of images from an array of cameras, each camera of the array of cameras having an overlapping field of view (FOV) with an adjacent camera of the array of cameras. The method further includes synchronously capturing a supplemental image from an additional camera, the additional camera having an at least partially overlapping FOV with every camera of the array of cameras. Supplemental information is extracted by comparing the supplemental image with the set of images. Portions of the set of images are stitched based in part on the supplemental information to produce a combined stitched image, the combined stitched image having a higher resolution than each image of the set of images.

A method and system are described. The method includes capturing a set of images from an array of cameras, each camera of the array of cameras having an overlapping field of view (FOV) with an adjacent camera of the array of cameras. The method further includes synchronously capturing a supplemental image from an additional camera, the additional camera having an at least partially overlapping FOV with every camera of the array of cameras. Supplemental information is extracted by comparing the supplemental image with the set of images. Portions of the set of images are stitched based in part on the supplemental information to produce a combined stitched image, the combined stitched image having a higher resolution than each image of the set of images.

A zooming control apparatus comprises an object detection unit configured to detect an object from an image; a first acquisition unit configured to acquire information regarding a distance to the object; and a zooming control unit configured to perform zooming control for automatically changing a zoom magnification according to at least one of second information that includes information regarding a size of the object detected by the object detection unit and first information regarding the distance to the object acquired by the first acquisition unit, wherein a condition for automatically changing the zoom magnification in the zooming control differs according to a reliability of the first information.

A zooming control apparatus comprises an object detection unit configured to detect an object from an image; a first acquisition unit configured to acquire information regarding a distance to the object; and a zooming control unit configured to perform zooming control for automatically changing a zoom magnification according to at least one of second information that includes information regarding a size of the object detected by the object detection unit and first information regarding the distance to the object acquired by the first acquisition unit, wherein a condition for automatically changing the zoom magnification in the zooming control differs according to a reliability of the first information.

The technology disclosed relates to relates to providing command input to a machine under control. It further relates to gesturally interacting with the machine. The technology disclosed also relates to providing monitoring information about a process under control. The technology disclosed further relates to providing biometric information about an individual. The technology disclosed yet further relates to providing abstract features information (pose, grab strength, pinch strength, confidence, and so forth) about an individual.