feature extraction

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 user interfaces;  diagnostic radiography;  medical image processing;  decision support systems;  decision making;  feature extraction;  image classification;  mammography;  medical expert systems;  neural nets;  statistical analysis;  tumours;  PMNN;  classified data points;  complementary machine observer;  computerized radiographic mass detection;  data points;  decision boundaries;  decision support;  enhanced segmentation;  featured database visualization;  featured knowledge database;  generalized normal mixtures;  hard clustering;  intelligent user interface;  interactive visualization hierarchy;  learning;  localized optimal displays;  machine learning tasks;  mammographic mass detection;  mapping;  mathematical feature extraction procedure;  modular neural networks;  optimal mapping;  probabilistic modular neural network;  probabilistic principal component projections;  radiologist performance;  soft clustering;  suspicious mass areas;  unclassified data points;  visual explanation;  

Abstract: We present a novel scheme to match a video clip against a large database of videos. Unlike previous schemes that match videos based on image similarity, this scheme matches videos based on similarity of temporal activity, i.e., it finds similar “actions”. Furthermore, it provides precise temporal localization of the actions in the matched videos. Video sequences are represented as a sequence of feature vectors called fingerprints. The fingerprint of the query video is matched against the fingerprints of videos in a database using sequential matching. The fingerprints are computed directly from compressed MPEG videos. The matching is much faster than real-time. We have used this scheme to find similar actions in sporting events, such as diving and baseball

 feature extraction;  image sequences;  actions similarity;  baseball;  compressed MPEG videos;  data compression;  diving;  feature vectors;  fingerprints;  image matching;  large video database;  query video;  sequential matching;  sporting events;  temporal activity similarity;  temporal localization;  video clip;  video coding;  video sequence matching;  visual databases;