Display device and display method thereof, electronic picture frame computer readable storage medium

Patent metadata

Field	Value
Publication number	US-10990800-B2
Application number	US-201816204193-A
Country	US
Kind code	B2
Filing date	Nov 29, 2018
Priority date	Apr 18, 2018
Publication date	Apr 27, 2021
Grant date	Apr 27, 2021

Abstract

The present disclosure relates to a display device and its display device, an electronic picture frame and a computer readable storage medium. The display device includes: a processor configured to acquire an environmental image of the environment where the display device is located, identify a category of the environmental image, and determine one or more pictures matching the category from a picture library; and a display configured to display at least one of the determined pictures.

First claim

What is claimed is:

1. A display device, comprising:
a processor configured to acquire an environmental image of the environment where the display device is located, recognize a category of the environmental image, and determine one or more pictures matching the category from a picture library, wherein the category comprises a decoration style, a decoration tone, and a furniture type of the environment; and
a display configured to display at least one of the determined one or more pictures.

2. The display device according to claim 1 , wherein the processor is configured to: recognize the category of the environmental image using a deep learning-based image recognition model.

3. The display device according to claim 1 , wherein the processor is configured to: determine the one or more pictures matching the category using a decision tree model.

4. The display device according to claim 3 , wherein the processor is configured to: determine the one or more pictures matching the category according to a priority of the category.

5. The display device according to claim 4 , wherein the priority of the category is ranked as decoration style>decoration tone>furniture type.

6. The display device according to claim 1 , wherein the display is configured to display a list of the one or more pictures and display the at least one of the one or more pictures in the list upon a user's selection.

7. The display device according to claim 1 , further comprising:
an image sensor configured to sense the environmental image of the environment where the display device is located.

8. A display method, comprising:
acquiring an environmental image of the environment where a display device is located;
recognizing a category of the environmental image, wherein the category comprises a decoration style, a decoration tone, and a furniture type of the environment;
determining one or more pictures matching the category from a picture library; and
causing the display device to display at least one of the determined one or more pictures.

9. The display method according to claim 1 , wherein the category of the environmental image is recognized using a deep learning-based image recognition model.

10. The display method according to claim 9 , wherein, according to the category of the environmental image, a corresponding input image is selected for training the image recognition model, the input image being labelled with a single label or multiple labels.

11. The display method according to claim 8 , wherein the one or more pictures matching the category is determined using a decision tree model.

12. The display method according to claim 11 , wherein the one or more pictures matching the category is determined according to a priority of the category, wherein the priority of category is ranked as decoration style>decoration tone>furniture type.

13. The display method according to claim 12 , wherein the determining one or more pictures matching the category from a picture library comprises:
sequentially determining which decoration style the environmental image belongs to, which decoration tone the environmental image belongs to, and which furniture type furniture in the environment belongs to; and
determining one or more pictures matching the decoration style, the decoration tone and the furniture type.

14. The display method according to claim 12 , further comprising:
constructing a training data set according to category labeling of decoration style, decoration tone and furniture type; and
constructing a decision tree model according to the training data set, to establish a mapping between the category and the training data set.

15. The display method according to claim 14 , wherein:
dividing labelled input images into three image sets according to the decoration style, the decoration tone and the furniture type;
training one classifier for each image set; and
making decisions based on results of voting by classifiers of the three image sets.

16. The display method according to claim 15 , wherein the making decisions based on results of voting by classifiers of the three image sets comprises:
starting from a root node of the decision tree model, dividing the decision tree model downwards layer by layer according to different categories until leaf nodes, to obtain decision results.

17. The display method according to claim 8 , further comprising:
causing the display device to display a list of the one or more pictures.

18. The display method according to claim 17 , wherein the at least one of the one or more pictures in the list is displayed upon a user's selection.

19. A display device, comprising:
a memory; and
a processor coupled to the memory, wherein the processor is configured to perform the display method according to claim 8 based on instructions stored in the memory.

20. A non-transitory computer readable storage medium on which a computer program is stored, wherein the program, when executed by a processor, implements the display method according to claim 8 .

Assignees

• Boe Technology Group Co Ltd

Inventors

• Wang Xiaohong

Classifications

• G06V10/82

  using neural networks · CPC title

• G06V10/809

  of classification results, e.g. where the classifiers operate on the same input data · CPC title

• G06V10/454

  Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN] · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06V20/64

  Three-dimensional [3D] objects · CPC title