Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction
نویسندگان
چکیده
منابع مشابه
Spatiotemporal Stacked Sequential Learning for Pedestrian Detection
Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestrian, while the responses around potential false positives are expected to be lower. An analogous reasoning applies for image sequences. If there is a pedestrian located within a frame, the same pedestrian is expected to...
متن کاملMethod for future pedestrian accident scenario prediction
This paper addresses future pedestrian accident scenarios involving next decade of small electric vehicles (SEVs) employed primarily in urban areas in 2025. The methodology used to predict the most relevant accident scenarios in 2025, in terms of speeds, impact locations, vehicle designs and inner-city boundaries, includes four main steps and as an example, the first three steps are shown for p...
متن کاملSpatiotemporal reasoning about epidemiological data
OBJECTIVE In this article, we propose new methods to visualize and reason about spatiotemporal epidemiological data. BACKGROUND Efficient computerized reasoning about epidemics is important to public health and national security, but it is a difficult task because epidemiological data are usually spatiotemporal, recursive, and fast changing hence hard to handle in traditional relational datab...
متن کاملPriority Order for Improvement of Intersections using Pedestrian Crash Prediction Model
One of the most important needs of pedestrians is safety at crossing points, especially at intersections. Intersections are important parts of the urban road network because any disruption in them reduces the capacity of the entire network. The main objective of this research is to propose an appropriate method for prioritizing urban intersections with considering the important factors affectin...
متن کاملContext-Based Pedestrian Path Prediction
We present a novel Dynamic Bayesian Network for pedestrian path prediction in the intelligent vehicle domain. The model incorporates the pedestrian situational awareness, situation criticality and spatial layout of the environment as latent states on top of a Switching Linear Dynamical System (SLDS) to anticipate changes in the pedestrian dynamics. Using computer vision, situational awareness i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Robotics and Automation Letters
سال: 2020
ISSN: 2377-3766,2377-3774
DOI: 10.1109/lra.2020.2976305