Canon Kabushiki Kaisha

Ashley John Partis

Amit Kumar Gupta

David Kenji See

Peter Jan Pakulski

Sridevan Parameswaran

Daniel John Wedge

Jorgen Peddersen

Hiroshi Tojo

Xin Yu Liu

Qianlu Lin

A system and method for performing foreground/background separation on an input image. The method identifies a corresponding model visual element in a scene model associated with the input image, the model visual element being associated with a set of element models, each element model including a plurality of visual data sets. Select an element model from the set of element models, dependent upon a visual distance between the input visual element and a visual data set of the selected element model satisfying a predetermined criterion. The method classifies the input visual element as one of foreground and background, dependent upon the selected element model, and then updates each visual data set in the selected element model, dependent upon the input visual element and at least first and second different methods of updating a visual data set.

Method for video object detection

A method for classifying a visual element in a video frame as either foreground or background, the video frame being characterized using a scene model comprising a plurality of modes, the method comprising the steps of: determining a blob boundary characteristic for a blob comprising at least the visual element; identifying a mode matched to the visual element; classifying the visual element and the matched mode as foreground dependent upon a match mode boundary characteristic of the matched mode; and updating the scene model dependent upon the blob boundary characteristic and the matched mode boundary characteristic.

Video segmentation method

Disclosed is a method of classifying visual elements in a region of a video as either foreground or background. The method classifies each visual element in the region as either foreground or background using a first classifier, and expands spatially at least one of the visual elements classified as foreground to form a spatially expanded area. The method then classifies the visual elements in the spatially expanded area as either foreground or background using a second classifier that is more sensitive to foreground than the first classifier.

A method of tracking objects of a scene is disclosed. The method determines two or more tracks which have merged. Each track is associated with at least one of the objects and having a corresponding graph structure. Each graph structure comprising at least one node representing the corresponding track. A new node representing the merged tracks is created. The graph structures are added as children nodes of the new node to create a merged graph structure. A split between the objects associated with one of the tracks represented by the nodes of the merged graph structure is determined. Similarity between one or more of the nodes in the merged graph structure and foreground areas corresponding to split objects is determined. One of the nodes in the merged graph structure is selected based on the determined similarity. A new graph structure for tracking the objects is created, the new graph structure having the selected node at the root of the new graph structure.

Method, system and apparatus for tracking objects of a scene

Disclosed are a method and apparatus for adjusting a set of luminance values associated with a set of visual elements in a current frame () of a video sequence for object detection (). The method determines (), for each of a plurality of scenarios (SO, SI, S2), a set of adjusted luminance values based on a corresponding luminance compensation value, and accumulates (), for each scenario, a set of brightness counts and darkness counts of the current frame based on the set of adjusted luminance values. A metric () is calculated for each scenario based on the set of brightness counts and darkness counts and one of scenarios is selected based on the calculated metric. The method then selects () the adjusted luminance value associated with the selected scenario as an adjusted set of luminance values associated with the current frame of the video sequence.

Method and system for luminance adjustment of images in an image sequence

Disclosed herein are a system and method for performing foreground/background separation on an input image. The method pre-classifies () an input visual element in the input image as one of a first element type and a second element type, dependent upon a predetermined characteristic. The method performs a first foreground/background separation () on the input visual element that has been pre-classified as the first element type, wherein the first foreground/background separation step is based on color data and brightness data of the input visual element. The method performs a second foreground/background separation () on the input visual element that has been pre-classified as the second element type, wherein the second foreground/background separation step is based on color data, brightness data, and texture of the input visual element.

Foreground background separation in a scene with unstable textures

Disclosed herein are a computer-implemented method and a camera system for determining a current spatial representation for a detection in a current frame of an image sequence. The method derives an expected spatial representation () for the detection based on at least one previous frame, generates a spatial representation () of the detection, and extends the spatial representation () to obtain an extended spatial representation (), based on the expected spatial representation (). The method determines a similarity measure between the extended spatial representation () and the expected spatial representation (), and then determines the current spatial representation for the detection based on the similarity measure.

Video object fragmentation detection and management

Disclosed herein are a computer-implemented method and a camera system for determining a current spatial representation for a detection in a current frame of an image sequence. The method derives an expected spatial representation () for the detection based on at least one previous frame, generates a spatial representation () of the detection, and extends the spatial representation () to obtain an extended spatial representation (), based on the expected spatial representation (). The method determines a similarity measure between the extended spatial representation () and the expected spatial representation (), and then determines the current spatial representation for the detection to based on the similarity measure.

A method of performing IPsec processing of an incoming communication packet is disclosed. The method comprises determining, from a received portion of the incoming packet, if sufficient information has been received to enable the IPsec processing to be commenced, obtaining the necessary information from the received portion of the packet, and commencing IPsec processing of said packet before the entire packet has been received depending upon the obtained information.

Concurrent IPsec processing system and method

A method for processing a packet comprising an ordered sequence of packet parts is disclosed. The method uses a set of hardware processing modules, and the method comprises the steps of broadcasting, in a step the next header field of a received packet part to the set of processing modules, and processing, in a step the received packet part by a sub-set of the modules dependent upon the broadcast next header field.

Modular approach to the TCP/IPv6 hardware implementation

An architecture for selectively powering a receive module () is disclosed. The architecture comprises the receive module () which is functionally adapted, while power is applied to the receive module () by a power module (), and after a power-up time interval has elapsed, to process a traffic packet. The architecture further comprises the power module () that is adapted to apply power to the receive moduledependent upon arrival of a wake-up packet.

Growing community of inventors

Liberty Grove, Australia

Ashley John Partis