.png){kind=icon}
Return
Sparse motion fields for trajectory prediction
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patcog.2020.107631.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Trajectory prediction is a crucial element of many automated tasks, such as autonomous navigation or video surveillance. To automatically predict the motion of an agent (e.g., pedestrian or car), the model needs to efficiently represent human motion and understand the external stimuli that may influence human behavior. In this work we propose a methodology to model the motion of agents in a video scene. Our method is based on space-varying sparse motion fields, which simultaneously characterize diverse motion patterns in the scene and implicitly learn contextual cues about the static environment, namely obstacles and semantic constraints. The sparse motion fields are applied to the task of long-term trajectory prediction using a probabilistic generative approach. Several benchmark data sets are used to demonstrate the potential of the proposed approach and show that our method achieves competitive state-of-the-art performances. (c) 2020 Elsevier Ltd. All rights reserved.
Keywords:
Human motion analysis
Trajectory prediction
Sparse motion fields
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.6
Papers:
1.3W
Citations:
4.5W
Organization
Cited Papers
A TUTORIAL ON HIDDEN MARKOV-MODELS AND SELECTED APPLICATIONS IN SPEECH RECOGNITION.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
ShareSaveShareSaveShareSaveRheumatology outcomes: the patient's perspective. A multicentre focus group interview study of Swedish rheumatoid arthritis patientsRheumatology
OAAI
RheumatologyIF0
OAAIShareSaveStructured dictionary learning for abnormal event detection in crowded scenesPATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
ShareSaveDetecting abnormal crowd behaviors based on the div-curl characteristics of flow fieldsPATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
ShareSaveCityTracker: Citywide Individual and Crowd Trajectory Analysis Using Hidden Markov ModelIEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
ShareSave
View more