G06V 10/80

Definition

Diese Klassifikationsstelle umfasst:

(Für diese Definition ist die deutsche Übersetzung noch nicht abgeschlossen)

Combining the information from several sources in order to form a unified representation for image or video recognition or understanding.

Notes – technical background

These notes provide more information about the technical subject matter that is classified in this place:

A simple fusion process combines raw data from several sensors or several sensor modalities (e.g. fusing spatial and temporal data). Besides fusing the raw sensor data, it is also possible to first process the sensor data to extract features and then combine the extracted features into a joint feature vector. Alternatively, it is possible to fuse classification results, e.g. inputting the features from different sensor modalities to separate classifiers, receiving respective classification scores from each classifier, and combining the individual scores into a final classification result.

Examples are probabilistic fusion, statistic fusion, fuzzy reasoning fusion, fusion based on evidence and belief theory, e.g. Dempster-Shafer, fusion by voting.

Fusion can also be applied at different stages of a recognition system for different purposes, e.g. for dimensionality reduction, computing robustness, improving precision and certainty in the classification decisions, etc.

Examples

Bildreferenz:G06V0010800000_0



Sensor-level fusion followed by classification

Bildreferenz:G06V0010800000_1



Feature-level fusion by combining colour, shape and texture representations.

Querverweise

Einschränkende Querverweise

Diese Klassifikationsstelle umfasst nicht:
Multimodal speaker identification or verification
G10L 17/10

Informative Querverweise

Pattern recognition or machine learning, using clustering
G06V 10/762
Pattern recognition or machine learning, using classification
G06V 10/764
Pattern recognition or machine learning, using regression
G06V 10/766

Glossar

Dempster-Shafer

general framework for reasoning with uncertainty which combines evidence from different sources and arrives at a degree of belief (represented by a mathematical object called belief function) that takes into account all the available evidence.