PATENT CLAIM ANALYSIS

Application Number: 15923511
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-09
Patent Classification: ["382", "158000"]

Abstract:
Systems and methods for estimating a layout of a room are disclosed. The room layout can comprise the location of a floor, one or more walls, and a ceiling. In one aspect, a neural network can analyze an image of a portion of a room to determine the room layout. The neural network can comprise a convolutional neural network having an encoder sub-network, a decoder sub-network, and a side sub-network. The neural network can determine a three-dimensional room layout using two-dimensional ordered keypoints associated with a room type. The room layout can be used in applications such as augmented or mixed reality, robotics, autonomous indoor navigation, etc.

Claim (Index 20):
A system comprising:\n non-transitory memory configured to store parameters for the neural network; and a hardware processor in communication with the non-transitory memory, the hardware processor programmed to:\n receive a training room image, wherein the training room image is associated with:\n a reference room type from a plurality of room types, and \n reference keypoints associated with a reference room layout; \n \n generate a neural network for room layout estimation, wherein the neural network comprises:\n an encoder-decoder sub-network configured to output predicted two-dimensional (2D) keypoints associated with a predicted room layout associated with each of the plurality of room types, and \n a side sub-network connected to the encoder-decoder network configured to output a predicted room type from the plurality of room types; and \n \n optimize a loss function based on a first loss for the predicted 2D keypoints and a second loss for the predicted room type; and \n update parameters of the neural network based on the optimized loss function.

Metadata:
- Claim Count in Document: 42.0
- Percentile: 90.0
- Lexical Diversity: 1.95161
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15481564', '15812928', '15815686', '15426727', '15817161']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3122474599256515
- 35 USC 102 Novelty (BERT): 0.4963857355792239
- Combined Prediction Score: 0.3306612874910087
- Mean Citation Score: 219.875826
- Max Citation Score: 255.73299
- Similarity Product: 194.27338658273567

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