PATENT CLAIM ANALYSIS

Application Number: 16199283
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["348", "159000"]

Abstract:
An approach for re-identifying an object in a test image is presented. Similarity measures between the test image and training images captured by a first camera are determined. The similarity measures are based on Bhattacharyya distances between feature representations of an estimated background region of the test image and feature representations of background regions of the training images. A transformed test image based on the Bhattacharyya distances has a brightness that is different from the test image's brightness and matches a brightness of training images captured by a second camera. An appearance of the transformed test image resembles an appearance of a capture of the test image by the second camera. Another image included in test images captured by the second camera is identified as being closest in appearance to the transformed test image and another object in the identified other image is a re-identification of the object.

Claim (Index 18):
The computer program product of  claim 13 , wherein the computer-readable program instructions, when executed by the CPU:\n determine, during the training mode, brightness transfer functions (BTFs) H i j  by determining H j \u22121 (H i (B i )), which is an inverted cumulative histogram, so that B j =H i j (B i ), which transfers a brightness value B i  in an object O i  to a corresponding brightness value B j  in an object O j , wherein object O i  is included in each first training image and object O j  is included in second training images captured by the second camera; determine, based on the Bhattacharyya distances, weights of the first training images captured by the first camera, the weights corresponding to the BTFs; determine, based on the Bhattacharyya distances, a weighted brightness transfer function (WBTF) by weighting the BTFs by the corresponding weights and combining the weighted BTFs; receive a threshold distance; receive K training images captured by the first camera; determine a first background region of the first test image; determine respective second background regions of each of the K training images captured by the first camera; determine first feature representations in the first background region of the first test image; and determine respective second feature representations in each of the second background regions, wherein the computer-readable program instructions that determine the measures of similarity includes computer-readable program instructions that, when executed by the CPU, determine K respective Bhattacharyya distances between the first feature representations in the first background region of the first test image and each of the second feature representations, wherein the computer-readable program instructions that determine the BTFs includes computer-readable program instructions that, when executed by the CPU, determine the BTFs after a determination of the K Bhattacharyya distances by an execution of computer-readable program instructions that determine the K Bhattacharyya distances, and computer-readable program instructions that, when executed by the CPU, select K BTFs from a plurality of BTFs, so that the K BTFs correspond to the K Bhattacharyya distances and so that each of the K Bhattacharyya distances is less than or equal to the threshold distance, wherein the computer-readable program instructions that determine the weights includes computer-readable program instructions that, when executed by the CPU, determine a matching cost \u03b1 k  corresponding to each of the K BTFs, wherein k=1, . . . , K, wherein the computer-readable program instructions that determine the WBTF includes computer-readable program instructions that, when executed by the CPU, weight each BTF of the K BTFs by the corresponding \u03b1 k  and computer-readable program instructions that, when executed by the CPU, determine a linear combination of the weighted K BTFs.

Metadata:
- Claim Count in Document: 44.0
- Percentile: 98.0
- Lexical Diversity: 2.5
- Patent Class: 348.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15471595', '13647645', '15634499', '14790323', '10966769']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6155835801552509
- 35 USC 102 Novelty (BERT): 0.5876099457113085
- Combined Prediction Score: 0.6127862167108566
- Mean Citation Score: 298.33274
- Max Citation Score: 467.33093
- Similarity Product: 461.276012490685

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test