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US 11,113,507 B2Granted
System and method for fast object detection
AssigneeSamsung Electronics Co., Ltd.
InventorsHeming Zhang, Xiaolong Wang, Jingwen Zhu
Life of this patent
Estimating the term…
Abstract
One embodiment provides a method comprising identifying a salient part of an object in an input image based on processing of a region of interest (RoI) in the input image at an electronic device. The method further comprises determining an estimated full appearance of the object in the input image based on the salient part and a relationship between the salient part and the object. The electronic device is operated based on the estimated full appearance of the object.
Claims18
A method comprising:
- identifying one or more salient parts of an object in an input image by classifying, at an electronic device, a set of input patches of the input image utilizing a multi-label classification network, wherein the multi-label classification network is trained to capture one or more global characteristics of the object and one or more local characteristics of the one or more salient parts of the object based on input patches cropped from a set of training images, the multi-label classification network classifies at least one input patch of the set of input patches as a first object classification representing a background, and the multi-label classification network classifies one or more other input patches of the set of input patches as one or more additional object classifications representing the one or more salient parts of the object;
- determining an estimated full appearance of the object in the input image based on the one or more salient parts and a relationship between the one or more salient parts and the object as defined by one or more bounding box templates for the one or more salient parts;
- and
- invoking an action on the electronic device based on the estimated full appearance of the object.
1 more element
A system comprising:
- at least one processor;
- and
- a non-transitory processor-readable memory device storing instructions that when executed by the at least one processor causes the at least one processor to perform operations including:
- identifying one or more salient parts of an object in an input image by classifying, at an electronic device, a set of input patches of the input image utilizing a multi-label classification network, wherein the multi-label classification network is trained to capture one or more global characteristics of the object and one or more local characteristics of the one or more salient parts of the object based on input patches cropped from a set of training images, the multi-label classification network classifies at least one input patch of the set of input patches as a first object classification representing a background, and the multi-label classification network classifies one or more other input patches of the set of input patches as one or more additional object classifications representing the one or more salient parts of the object;
- determining an estimated full appearance of the object in the input image based on the one or more salient parts and a relationship between the one or more salient parts and the object as defined by one or more bounding box templates for the one or more salient parts;
- and
- invoking an action on the electronic device based on the estimated full appearance of the object.
4 more elements
A non-transitory computer readable storage medium including instructions to perform a method comprising:
- identifying one or more salient parts of an object in an input image by classifying, at an electronic device, a set of input patches of the input image utilizing a multi-label classification network, wherein the multi-label classification network is trained to capture one or more global characteristics of the object and one or more local characteristics of the one or more salient parts of the object based on input patches cropped from a set of training images, the multi-label classification network classifies at least one input patch of the set of input patches as a first object classification representing a background, and the multi-label classification network classifies one or more other input patches of the set of input patches as one or more additional object classifications representing the one or more salient parts of the object;
- determining an estimated full appearance of the object in the input image based on the one or more salient parts and a relationship between the one or more salient parts and the object as defined by one or more bounding box templates for the one or more salient parts;
- and
- invoking an action on the electronic device based on the estimated full appearance of the object.
1 more element
Dependencies are inferred from the claim text.