| CPC G06Q 30/02 (2013.01) [G06F 3/013 (2013.01); G06Q 30/0276 (2013.01); G06T 7/0002 (2013.01); G06T 7/70 (2017.01); G06T 7/90 (2017.01); G06T 11/001 (2013.01); G06T 17/00 (2013.01); G06V 10/20 (2022.01); G06V 10/40 (2022.01); G06V 10/56 (2022.01); G06V 10/82 (2022.01); G06V 20/63 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06V 2201/09 (2022.01)] | 14 Claims |
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1. A processor-implemented method of recognizing a plurality of objects of a design creative within an environment, analyzing the plurality of objects using a deep neural networking model and generating a modified design creative based on the analysis, the method comprising:
generating a database with a media content associated with an environment, wherein the media content is captured using a camera, wherein the media content comprises at least one of an image of a design creative, a video of a design creative, a shelf design creative, a point of sale material creative, a digital advertisement creative or an image, a video or a three-dimensional model of at least one of a physical retail store environment, a digital retail store environment, a virtual reality store environment, a social media environment or a web page environment;
determining a location of a design creative within the media content associated with the environment;
determining, using a deep neural networking model, at least one object from the design creative within the environment, wherein said at least one object comprises at least one of a brand name, a brand logo, a text, a product or a brand-specific object, wherein the deep neural networking model is trained using a plurality of design creatives taken at a plurality of instances corresponding to a plurality of brands, wherein the training of the deep neural networking model comprises providing a collection of a user's eye movement on the design creative within the environment in which the design creative is placed using a headset and a recorded video with corresponding eye movement of the user, wherein the user's eye movement comprises an eye fixation, an amount of eye fixation and a sequence of eye fixation;
determining at least one attribute of at least one object within the media content associated with the environment using a deep neural networking model, wherein said at least one attribute comprises a color, a color contrast, a location of the object, a text size, or a number of words in the text;
implementing at least one compliance rule to the at least one attribute of the at least one object to determine at least one of a number of words in the text, a size of the brand logo or the brand name, a location of the brand logo or the brand name, a color contrast of a design creative in context of other design creative, a distinctness and an effectiveness of the brand product with respect to the environment, wherein said at least one compliance rule comprises at least one of a text compliance, a color compliance, a location compliance or a size compliance;
generating an attention sequence and a heatmap for the media content associated with the environment using the deep neural networking model, wherein attention sequence comprises a sequence number for a plurality of pixel in the media content and the heatmap comprises a heat for a plurality of different color of the plurality of pixels in the media content;
plotting an eye fixation on an image of the recorded video of the media content;
coloring the plurality of pixel of the media content with a different color; and
numbering each pixel of the media content with a sequence number, wherein the coloring of the plurality of pixel of the design creative with the different color signifies different heat on the design creative within the environment, wherein the attention sequence is generated using the numbering of each pixel of the media content, and wherein the attention heatmap is generated using different heat colors of the plurality of pixels in the media content associated with the environment;
automatically generating, using the deep neural networking model, a first recommendation for modifying the at least one object of the design creative within the environment based on the at least one compliance rule, the attention sequence and the heatmap obtained corresponding to the design creative, wherein the first recommendation for modifying at least one least one object comprises at least one of a text prescription, a brand prescription, a brand color prescription or a product compliance; and
automatically generating, using the deep neural networking model, a modified design creative for the environment based on the attention heatmap, the attention sequence and the generated first recommendation.
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