期刊
JOURNAL OF REAL-TIME IMAGE PROCESSING
卷 10, 期 4, 页码 785-803出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11554-014-0428-8
关键词
Human interactions; Motion prediction; Behavior understanding; Crowd analysis; Gaussian mixture models
类别
资金
- Artemis JU
- UK Technology Strategy Board through COPCAMS Project [332913]
We present an extensive survey of methods for recognizing human interactions and propose a method for predicting rendezvous areas in observable and unobservable regions using sparse motion information. Rendezvous areas indicate where people are likely to interact with each other or with static objects (e.g., a door, an information desk or a meeting point). The proposed method infers the direction of movement by calculating prediction lines from displacement vectors and temporally accumulates intersecting locations generated by prediction lines. The intersections are then used as candidate rendezvous areas and modeled as spatial probability density functions using Gaussian Mixture Models. We validate the proposed method to predict dynamic and static rendezvous areas on real-world datasets and compare it with related approaches.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据