首页>
外国专利>
Intra-trajectory anomaly detection using adaptive voting experts in a video surveillance system
Intra-trajectory anomaly detection using adaptive voting experts in a video surveillance system
展开▼
机译:在视频监控系统中使用自适应投票专家进行轨迹内异常检测
展开▼
页面导航
摘要
著录项
相似文献
摘要
A sequence layer in a machine-learning engine configured to learn from the observations of a computer vision engine. In one embodiment, the machine-learning engine uses the voting experts to segment adaptive resonance theory (ART) network label sequences for different objects observed in a scene. The sequence layer may be configured to observe the ART label sequences and incrementally build, update, and trim, and reorganize an ngram trie for those label sequences. The sequence layer computes the entropies for the nodes in the ngram trie and determines a sliding window length and vote count parameters. Once determined, the sequence layer may segment newly observed sequences to estimate the primitive events observed in the scene as well as issue alerts for inter-sequence and intra-sequence anomalies.
展开▼