BR102016000694A2 - Device for creating a moscow of reconstructed images and method for creating a mosaic of reconstructed images - Google Patents

Device for creating a moscow of reconstructed images and method for creating a mosaic of reconstructed images Download PDF

Info

Publication number
BR102016000694A2
BR102016000694A2 BR102016000694-5A BR102016000694A BR102016000694A2 BR 102016000694 A2 BR102016000694 A2 BR 102016000694A2 BR 102016000694 A BR102016000694 A BR 102016000694A BR 102016000694 A2 BR102016000694 A2 BR 102016000694A2
Authority
BR
Brazil
Prior art keywords
tn
image
blocks
mosaic
background
Prior art date
Application number
BR102016000694-5A
Other languages
Portuguese (pt)
Inventor
Monteiro Passos Graciliano
Original Assignee
Up Points Serviços Empresariais S.A.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Up Points Serviços Empresariais S.A. filed Critical Up Points Serviços Empresariais S.A.
Priority to BR102016000694-5A priority Critical patent/BR102016000694A2/en
Publication of BR102016000694A2 publication Critical patent/BR102016000694A2/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20Image acquisition
    • G06K9/34Segmentation of touching or overlapping patterns in the image field
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • G06K9/4642Extraction of features or characteristics of the image by performing operations within image blocks or by using histograms
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/08Logistics, e.g. warehousing, loading, distribution or shipping; Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00Payment architectures, schemes or protocols
    • G06Q20/08Payment architectures
    • G06Q20/20Point-of-sale [POS] network systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/06Buying, selling or leasing transactions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/50Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/187Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00Details of television systems
    • H04N5/222Studio circuitry; Studio devices; Studio equipment ; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, TV cameras, video cameras, camcorders, webcams, camera modules for embedding in other devices, e.g. mobile phones, computers or vehicles
    • H04N5/262Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed circuit television systems, i.e. systems in which the signal is not broadcast
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/08Logistics, e.g. warehousing, loading, distribution or shipping; Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G06Q10/087Inventory or stock management, e.g. order filling, procurement, balancing against orders

Abstract

device for creating a mosaic of reconstructed images and method for creating a mosaic of reconstructed images. The present invention relates to a device for creating a reconstructed image mosaic comprising an image capture means and a processing medium. the image capture means (200) is programmed to continuously capture image frames from a display device (100) with articles (120) at different times of time. The processing medium analyzes this series of images and creates a mosaic of reconstructed images that reflects the actual state of the articles on the display device at a given time tn, even if the image frame actually captured at that time tn includes obstructions in front of the images. articles.

Description

"DEVICE FOR CREATING A RECONSTRUCTED IMAGES MOSAIC AND METHOD FOR CREATING A RECONSTRUCTED IMAGES MOSAIC" FIELD OF THE INVENTION

The present invention relates to a device and method for creating a reconstructed image mosaic and, more specifically, the present invention relates to a device and methods for creating a reconstructed image mosaic that can be be used in an inventory management system based on object recognition analysis.

BACKGROUND OF THE INVENTION

[002] Inventory control is one of the essential activities related to retail trade. Inefficient inventory management can lead to delays in stock replenishment orders, improper or confusing display of products at points of sale, or even complete stockouts.

[003] For retailers, inventory issues can lead to increased replacement costs (late / unnecessary orders and stock imbalances), loss of revenue due to lack of consumer desired product, or a sloppy store aspect with empty shelves. or no product diversity.

[004] For the supplier, the absence of their product at the point of sale may affect consumer behavior or loyalty - which may choose to buy another brand - and disrupt marketing efforts linked to the point of sale product display layout. . Similarly, lack of inventory control can lead to inefficient logistics planning based on erroneous sales / inventory information.

The most widespread inventory management systems usually involve manual labor, where an employee is assigned to periodically check products on display at points of sale and products in stock, generating data for the preparation of planograms and reports of control.

As known to those skilled in the art, planograms are graphical representations of articles (products) on gondolas or shelves. These representations are used for planning products displayed at the point of sale to manage product sales and replacements.

[007] This manual inventory control has been proving inefficient: besides being a slow and laborious procedure, it does not produce the expected results. For hand-generated reporting to come true, enough staff would have to be allocated to check the entire point of sale at very short intervals. Of course, this type of check procedure is not feasible.

In addition, even if this optimal check procedure were possible, the time elapsed between physical point-of-sale verification, processing of information gathered with inventory information, reporting, and analysis of reports would already be greater than ideal time for dynamic decision making.

In view of the drawbacks mentioned above, automated inventory management solutions are being developed, generally based on point-of-sale image recognition techniques.

[010] US2003 / 0154141, for example, shows an image recognition based inventory management system. In this system, video cameras are installed in the aisles of the point of sale to transmit data about the products on display. The cameras are linked with image recognition software that recognizes the missing or low quantity products and allows a planogram of the displayed products to be updated. Communication between the cameras and the processing computer is via a LAN or a WAN network. For image recognition to be possible, a central computer also includes a database of stored images of all point-of-sale products.

[011] Document PI 0816173-9 is a planogram extraction method based on image processing. For the implementation of the method, one or more image capture devices are installed in inventory environments, object recognition analysis is performed on the captured image, and a planogram is extracted based on the image recognition data.

Although the above solutions are an evolution over manual inventory control, image recognition based management methods have some drawbacks.

[013] A first of these drawbacks is related to analysis of the image captured at points of sale. For the recognition analysis to be performed, it is necessary that the image captured by the cameras at the point of sale allows the visualization of the articles on the shelves or gondolas. Because supermarket aisles or other businesses are places of movement with constant traffic from consumers or employees, there is a high likelihood that captured images will have obstructions that prevent viewing of products.

[014] This inconvenience leads to the need for pre-selection of images to be used for recognition or the need for the captured image to be worked out for cleaning or correction of the captured image.

[015] In an attempt to solve this problem, the method of PI 0816173-9 mentions the possibility of detecting image obstructions during image analysis - several of the prior art obstruction detection techniques are cited. in the document - and discard or ignore the image or part of the image that is jammed.

[016] Another drawback present in object recognition based inventory management methods is related to the transmission of image data.

[017] Known methods involve the transmission of images captured at the point of sale to image analysis servers. It is generally desirable for image capture devices to be wireless and for images to be transmitted to the analysis server over wireless networks, such as LAN, WAN, or other Internet Protocol networks.

[018] As those skilled in the art know, object recognition analysis should be performed on high resolution images, which by definition are heavy images.

[019] Heavy image transmission puts pressure on network upload links. Thus, a limit is created on the number of images and frames that the upload link can support, which imposes restrictions on the number of images that will actually be object of the recognition analysis. That is, while the image capture device can capture images every second of the 24 hours of a day, a natural limit is imposed on the amount of images that can actually be sent for object recognition analysis.

[020] Another drawback of inventory management methods based on object recognition in images is the need to respect consumer privacy. In fact, some countries have laws that prevent establishments from obtaining consumer images for any purpose other than for security monitoring alone. Thus, legislation prevents a point-of-sale captured image showing a consumer in the aisle or near a gondola or shelf from being sent to an image analysis server. This kind of legal impediment renders inapplicable some of the solutions known in the art. OBJECTIVES OF THE INVENTION

It is an object of the present invention to provide a device and method of constructing an image mosaic for application in object recognition based inventory management systems that solves problems related to the state of the art.

It is another object of the present invention to provide a device and method of constructing an image mosaic that provides a file size image mosaic suitable for internet traffic.

It is yet another object of the present invention to provide a device and method of constructing an image mosaic that enables the construction of an image mosaic showing the articles being displayed at a point of sale without obstruction of the articles.

It is a further object of the present invention to provide a device and method of constructing an image mosaic that enables the construction of an image mosaic that excludes any persons who might be in range of the image capture devices at the moment. of image capture.

BRIEF DESCRIPTION OF THE INVENTION

[025] The present invention achieves the above objectives by means of a device for creating a reconstructed image mosaic comprising an image capture means and a processing medium.

[026] The image capture medium is programmed to continuously capture image frames from a display device with articles at different times of time. Thus, for a series of captured image frames, tn represents a reference time moment, tn- is the past time, and tn + is the future time.

[027] The processing medium analyzes this series of images to identify, for each frame at time tn, background blocks that have changed relative to the other background blocks in the series of images at time tn- and tn +. Background blocks as used herein are blocks that show only the background elements of the picture frame, that is, the display device and the articles packed there.

The mosaic making device of the present invention utilizes such background image blocks to construct, for each time tn, a reconstructed image mosaic. Thus, for the reference time tn, this image mosaic includes: [029] the reproduction of blocks of background elements that showed changes in the series of frames captured at times tn-; and [030] including background blocks that have shown changes in time tn, provided that such background blocks do not change relative to the corresponding background blocks in frames captured at time tn +.

Thus, each reconstructed image mosaic created can reflect the actual state of the articles in the time display tn, even if the effectively captured time frame tn includes obstructions in front of the articles (such obstructions could include, for example, people or objects standing or moving in front of the display device).

[032] The device of the present invention also provides for the creation of metadata associated with each background block that changes relative to the other background blocks in the image series at times tn- and tn +. Such metadata may include, for example, the indication of background change, the presence of a stationary shape in front of the display device, or the presence of a moving shape on the display device.

[033] The device of the present invention may also comprise a means for compressing the created reconstructed image mosaics, for example, allowing such mosaics to reach a size suitable for transmission via the internet or wireless networks. Compression also allows the created tiles to take up less storage space and to process them with smaller CPUs.

The present invention also provides for the creation of feature maps associated with the generated reconstructed image mosaics. In an object recognition-based inventory management system, object recognition analysis will be performed on this feature map. It should be noted that the metadata created by the device and method of the present invention can further optimize object recognition analysis, as the metadata can indicate exactly where changes are for each tn buffer, allowing analysis to be performed only for those objects. blocks where there was change.

The further advantages of the device and method of the present invention will be apparent from the detailed description of the exemplary embodiment shown in the figures.

BRIEF DESCRIPTION OF DRAWINGS

[036] The present invention will be described in more detail below, with reference to the accompanying drawings, in which: [037] Figure 1 - is a schematic illustration of an image recognition based inventory management system utilizing the tracking device. according to a preferred embodiment of the present invention;

[038] Figure 2 is a schematic illustration of the logic underlying the image mosaic creation method according to a preferred embodiment of the present invention;

Figure 3 is an example of an image mosaic constructed with the device of the present invention; and [040] Figure 4 is a schematic illustration of an application of the image mosaic maker in accordance with the present invention. DETAILED DESCRIPTION OF THE INVENTION

[041] The present invention will be described hereinafter based on an example of preferred embodiment.

[1] Figure 1 is a schematic illustration of an inventory management system using the image tessellation device of the present invention.

[043] The figure schematically illustrates an article display device 100 at a point of sale, with a consumer 110 next to the display device 100. Items or products 120 are disposed on the display device 100.

It should be noted that although a shelf 100 is illustrated, the present invention could be used with any kind of packaging or display means for articles or products, such as gondolas, refrigerators, carton displays and the like.

Furthermore, while the present invention is exemplarily described herein in relation to display of sales products, it should be noted that the device and method of the present invention may be applied to any inventory management system where articles are packaged in devices. such as industrial inventory inventories or spare parts inventories.

[046] Turning to Figure 1, one or more mosaic making devices 200 are arranged at the point of sale. Although the figure schematically illustrates only one device 200, it should be understood that a single point of sale environment may include a plurality of mosaic making devices 200.

[047] In addition, it should be understood that the mosaic making device 200 may be statically fixed to a point in the environment or may be on fixed or movable support means.

[048] In the preferred embodiment of the present invention, the moisaic circling device 200 comprises a sequential image capture means, a processing unit, a processing RAM memory, mosaic transmission means and a storage medium which stores the operating system and processing software.

[049] The image capture medium may be, for example, a USB camera, a complementary metal oxide semiconductor (CMOS) sensor or a charged coupled device (CCD) with a control coupling module, or any other suitable capture medium. of images in sequence.

[050] The processing unit may be a low-power CPU, such as an ARMv7 architecture CPU. Of course, similar low-consumption processing units could also be used.

Mosaic transmission media may comprise, for example, ethernet card, cable, or Wi-Fi module, or wireless media.

The storage device may be, for example, an SSD card or similar storage devices or media.

[053] Mosaic device 200, the operation of which will be described in detail later, continuously captures real-time image frames from shelf 100 and creates a reconstructed image mosaic - schematically illustrated with reference numeral 210 - of articles 120 on shelf 100, eliminating any obstructions in front of shelf 100, such as person 110. That is, the image mosaic created is a mosaic illustrating an actual representation of the "background" of the captured image frames.

[054] The tile maker 200 creates a tile or a compressed tile block. This compressed data has a file size suitable for wireless networking. To have an understanding of the efficiency of the technique, 24h capture takes up less than 200MB, and without any compression only 50 frames would take up over 200MB.

[055] The reconstructed background mosaic 210 is sent to a processing system that includes a feature map generator or feature maps 300 for creating a feature map 310.

As known to those skilled in the art, feature maps are maps that extract visual features from an image, such as color, shape and texture, borders, lines, and index such features. Feature maps are common in content-based image retrieval systems (SRIBCs) or image analysis systems for understanding the environment (3D map extraction, motion detection, change detection).

[057] The created feature maps are then sent to a feature map server 320 and are accessed for performing object recognition analyzes that will enable inventory and inventory breakdown analyzes.

[058] As shown in Figure 1, the inventory management system further has inventory analysis 400 and stretch break analysis 500 servers. The system further comprises a database 600. Analysis servers 400, 500 and The 600 database can be accessed by 700 users.

Figure 2 is a schematic flow diagram of the operation of the mosaic creation method of the present invention.

[060] Mosaic device 200 captures, in real time, a series of image frames at different time points from shelf 100 with articles 120. The series of image frames over time is illustrated in Figure 2. as t1, t2, t3, t4, t5 and t6, where tn is the capture time. Note that tn can continue indefinitely as picture frames are captured continuously.

Thus, in one embodiment of the present invention, the device captures sequences of 4 frames per second, where T0 = 0s, T1 = 250ms, T2 = 500ms, T3 = 750ms, T4 = 1s, T5 = 1s250ms, T6 = 1 , 5s, etc. Thus, the device of the present invention is capable of capturing a large number of frames in a time interval, which allows the mosaic in a given Tn to be created from the temporal analysis of a large number of frames.

[062] The number of frames analyzed for creating a mosaic for a captured series will depend on the processing capacity available on the mosaic maker 200.

[063] As can be seen from the illustration, the example sequence of frames can be defined as follows: [064] t1: initial captured image frame of the example, where the present article a1 is noted;

[065] t2: time-captured picture frame t2, where article a1 present at t1 is not present on the shelf;

[066] t3: Image frame captured at time t3, where article a1 is still missing;

[067] t4: picture frame captured at time t4, where article a1 is still missing but part of the background is obstructed by the presence of a person;

[068] t5: time frame captured at time t5, where part of the background is obstructed by the presence of a person and where it is not possible to know whether article a1 is present or absent; and [069] t6: time frame captured at time t6, where it can be seen that article a1 is still missing and article a2, which was present at t4 and obstructed at t5, is missing.

In the mosaic creation method of the present invention, an algorithm is used to do a pixel block analysis of the image sequence. In the embodiment of the present invention, the images are worked in YUV format.

[071] The algorithm used can identify changes in the background and the permanence or not of those changes during that series analyzed. Thus, the algorithm can realize that: there was a change in the bottom of the image (shelf + articles) between t1 and t2; whereas although there is an obstruction by one person at t4, there was no change in the background of the image between t4 and t3; and although it has an obstruction by one person at t5, there was a change in the background between t4 and t5.

[072] This perception in the absence of background change in t4 is only possible because the algorithm does not just do a simple or piecemeal analysis between tn and tn-1 images, the algorithm analyzes the entire frame sequence to realize that changes deep down they were permanent.

Thus, the processing medium of the device of the present invention is capable of analyzing a frame series of images captured at different time points tn-, tn, tn +, where tn is a reference time moment, tn- moments of time in the past and tn + are moments of time in the future.

[074] For each frame at time tn, the background blocks that have changed relative to the other background blocks in the series of images at times tn- and tn + are identified.

[075] The image mosaic is constructed from the reproduction of blocks of background elements that present changes in the series of frames captured at times tn-; and including background blocks that have shown changes in time tn, provided that such background blocks show no change from background blocks in frames captured at times tn +.

[076] Figure 3 shows an image mosaic 210 created by the mosaic maker of the present invention for time tn = t5. The mosaic was reconstructed using the block of changes identified in the image captured at time t2 and the block of changes identified in time t5 (note that this block of background elements shows no changes from t6).

[077] In this regard, it should be noted that in this reconstructed background mosaic, the person causing obstruction is not present. That is, the mosaic is not the image frame captured at t5, but rather a representation of the actual condition of articles 120 on shelf 100 at time t5.

[078] This perception of time t5 is only possible because the analysis algorithm considered the sequence that goes beyond t5 and was able to perceive that a person blocking the bottom at t5 removed article a2 from the shelf.

Thus, mosaic 210 created for time t5 contains background blocks that can be generated from image frames captured at different times. In this way, each tile block contains unobstructed, non-moving background elements. Therefore, the mosaic created for time t5 is not an image at time t5 but a reconstruction of the background elements from blocks originating from different frames captured at different times.

[080] The tile maker also allows metadata to be created with information about the blocks used for tile construction. Thus, metadata may contain information about changes in background elements and about movements and shapes in front of that background (eg, people passing, obstructions by objects, etc.).

As illustrated in Figure 2, the method of the present invention allows the creation of reconstructed background mosaic blocks M2, M4, M5, M6 with metadata of information on background changes and presence and movement of shapes in front of the background.

[082] Note that these blocks do not include images at times t2, t4, t5 and t6 but rather mosaics that reconstruct static background elements at times t2, t4, t5 and t6.

[083] As can be seen from the flowchart of Figure 4, these reconstructed background blocks and metadata are compressed and stored.

[084] Compression is optimized by considering the tile blocks where changes have actually occurred. This allows a reduction in processing capacity, which allows for a reduction in costs and time.

[085] Mosaic compression is preferably performed by an image compression codec that works with YUV pixels. This feature allows a saving in the processing power required by the mosaic maker 20, since the previous step already works with data. in YUV format, without requiring large volume conversions.

[086] Block mosaics where significant changes have occurred are used for feature map extraction, as discussed in relation to Figure 1.

[087] Object recognition analysis is performed on feature maps, considering metadata with information about changes in areas.

Thus, the device and tiling method of the present invention provides, in addition to not only optimizing the file size for data transmission and reducing the processing power required, faster object recognition analysis. it is efficient.

Having described an example of a preferred embodiment of the present invention, it should be understood that the scope of the present invention encompasses other possible variations of the described inventive concept, being limited only by the content of the appended claims, including the possible equivalents thereof.

Claims (9)

  1. Apparatus for creating a reconstructed image mosaic comprising an image capture means for continuously capturing image frames of a display device (100) with a plurality of articles (120) and a processing medium which performs an algorithm to: analyze a frame series of images captured at different time points tn-, tn, tn +, where tn is a reference time moment, tn- are past time moments and tn + are past time moments. future; identify, for each frame at time tn, blocks of background elements that have changed relative to the other blocks of background elements in the series of images at times tn- and tn +, construct, for each time tn, a mosaic of reconstructed images with : - the reproduction of blocks of background elements that show changes in the series of frames captured at times tn-; and including background blocks that have shown changes in time tn, provided that such background blocks do not change relative to background blocks in frames captured at times tn +.
  2. Device according to Claim 1, characterized in that the processing means creates for each background block that changes relative to the other background blocks in the image series at times tn- and tn +, a metadata associated with identified change information.
  3. Device according to claim 2, characterized in that the processing means further comprises a means for compressing the created reconstructed image tiles.
  4. Device according to any one of claims 1 to 3, characterized in that the processing medium creates a feature map corresponding to each reconstructed image mosaic created.
  5. Device according to any one of claims 1 to 4, characterized in that the tessellation device (200) comprises a sequential image capture means, a processing unit, a storage medium, a RAM memory, and a processing and means for transmitting the mosaics.
  6. Method for creating a mosaic of reconstructed images, comprising: continuously capturing image frames from a display device (100) with a plurality of articles (120); analyze a frame series of images captured at different time points tn-, tn, tn +, where tn is a reference time moment, tn- are past time moments and tn + are future time moments; identify, for each frame at time tn, blocks of background elements that have changed relative to the other blocks of background elements in the series of images at times tn- and tn +, construct, for each time tn, a mosaic of reconstructed images with : - the reproduction of blocks of background elements that show changes in the series of frames captured at times tn-; and including background blocks that have shown changes in time tn, provided that such background blocks do not change relative to background blocks in frames captured at times tn +.
  7. Method according to claim 6, characterized in that it further comprises creating a metadata associated with each background block that changes relative to the other background blocks in the image series at times tn- and tn + , where metadata includes information about the identified change.
  8. Method according to claim 7, characterized in that it further comprises the step of compressing the created reconstructed image mosaics.
  9. A method according to any one of claims 6, further comprising: creating a feature map corresponding to each reconstructed image mosaic created.
BR102016000694-5A 2016-01-13 2016-01-13 Device for creating a moscow of reconstructed images and method for creating a mosaic of reconstructed images BR102016000694A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
BR102016000694-5A BR102016000694A2 (en) 2016-01-13 2016-01-13 Device for creating a moscow of reconstructed images and method for creating a mosaic of reconstructed images

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
BR102016000694-5A BR102016000694A2 (en) 2016-01-13 2016-01-13 Device for creating a moscow of reconstructed images and method for creating a mosaic of reconstructed images
PCT/BR2016/050303 WO2017120651A1 (en) 2016-01-13 2016-11-23 Device for creating mosaics of reconstructed images and method for creating a mosaic of reconstructed images

Publications (1)

Publication Number Publication Date
BR102016000694A2 true BR102016000694A2 (en) 2017-07-18

Family

ID=59310575

Family Applications (1)

Application Number Title Priority Date Filing Date
BR102016000694-5A BR102016000694A2 (en) 2016-01-13 2016-01-13 Device for creating a moscow of reconstructed images and method for creating a mosaic of reconstructed images

Country Status (2)

Country Link
BR (1) BR102016000694A2 (en)
WO (1) WO2017120651A1 (en)

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1436742A1 (en) * 2001-09-18 2004-07-14 Pro-Corp Holdings International Limited Image recognition inventory management system
US8009864B2 (en) * 2007-08-31 2011-08-30 Accenture Global Services Limited Determination of inventory conditions based on image processing
US7949568B2 (en) * 2007-08-31 2011-05-24 Accenture Global Services Limited Determination of product display parameters based on image processing
US8630924B2 (en) * 2007-08-31 2014-01-14 Accenture Global Services Limited Detection of stock out conditions based on image processing
US20140003655A1 (en) * 2012-06-29 2014-01-02 Praveen Gopalakrishnan Method, apparatus and system for providing image data to represent inventory
US9380222B2 (en) * 2012-12-04 2016-06-28 Symbol Technologies, Llc Transmission of images for inventory monitoring

Also Published As

Publication number Publication date
WO2017120651A1 (en) 2017-07-20

Similar Documents

Publication Publication Date Title
Georgakopoulos et al. Internet of Things and edge cloud computing roadmap for manufacturing
US10089595B2 (en) Systems and methods for supply chain event visualization
Ma et al. Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra-and inter-category promotional information
US9711182B2 (en) System and method for identifying and altering images in a digital video
Corsini et al. Perceptual metrics for static and dynamic triangle meshes
US20150206081A1 (en) Computer system and method for managing workforce of employee
CN103559636B (en) Restaurant management system based on cloud computing and intelligent analysis
US10129507B2 (en) System and method for self-checkout using product images
US9886678B2 (en) Graphic representations of planograms
WO2017128982A1 (en) Optical tag-based information interaction system and method therefor
US10127438B1 (en) Predicting inventory events using semantic diffing
CN109154993A (en) System and method for positioning, identifying and counting to article
US8479975B2 (en) System and method for using machine-readable indicia to provide additional information and offers to potential customers
JP5314199B1 (en) Customer segment analysis apparatus, customer segment analysis system, and customer segment analysis method
JP5356615B1 (en) Customer behavior analysis device, customer behavior analysis system, and customer behavior analysis method
US9124778B1 (en) Apparatuses and methods for disparity-based tracking and analysis of objects in a region of interest
EP3163872B1 (en) Flow line analysis system, camera device, and flow line analysis method
JP2014002722A (en) Comparing virtual and real images in shopping experience
JP6424225B2 (en) System and method for predicting consumer location in a retail facility
US20150095189A1 (en) System and method for scanning, tracking and collating customer shopping selections
US9418352B2 (en) Image-augmented inventory management and wayfinding
US20130117153A1 (en) Fully interactive, wireless, retail video display tag, integrated with content distribution, data management, feedback data collection, inventory and product price search capabilities
US10614514B2 (en) Computer vision system and method for automatic checkout
US20130030875A1 (en) System and method for site abnormality recording and notification
US9659272B2 (en) Method and apparatus for managing product placement on store shelf

Legal Events

Date Code Title Description
B03A Publication of an application: publication of a patent application or of a certificate of addition of invention
B25G Requested change of headquarter approved

Owner name: UP POINTS SERVICOS EMPRESARIAIS S.A. (BR/SC)