Covariance Features for Trajectory Analysis
نویسندگان
چکیده
منابع مشابه
Smoothness analysis for trajectory features
Dynamic modeling of speech is potentially a major improvement on Hidden Markov Models (HMMs). In one approach, trajectory models[1] are used to model the dynamics of the spectrum, and are used as basis for classi cation [1, 2]. Although some improvement has been achieved in this way, one would hope for more substantial improvements given that the independence assumption is removed. One reason w...
متن کاملOptimized Cascade of Classifiers for People Detection using Covariance Features
People detection on static images and video sequences is a critical task in many computer vision applications, like image retrieval and video surveillance. It is also one of most challenging task due to the large number of possible situations, including variations in people appearance and poses. The proposed approach optimizes an existing approach based on classification on Riemannian manifolds...
متن کاملCross-Covariance-based Features for Speech Classification in Film Audio
As multimedia becomes the dominant form of entertainment through an ever increasing range of digital formats, there has been a growing interest in obtaining information from entertainment media. Speech is one of the core resources in multimedia, providing a foundation for the extraction of semantic information. Thus, detecting speech is a critical first step for speech-based information retriev...
متن کاملIdentifying Driver Behaviors using Trajectory Features for Vehicle Navigation
We present a novel approach to automatically identify driver behaviors from vehicle trajectories and use them for safe navigation of autonomous vehicles. We propose a novel set of features that can be easily extracted from car trajectories. We derive a data-driven mapping between these features and six driver behaviors using an elaborate web-based user study. We also compute a summarized score ...
متن کاملLearning animal social behavior from trajectory features
Automatically classifying behavior of humans and animals from video is one of the most interesting and challenging fields of computer vision, [3, 1, 6]. Most of the successful human behavior recognition works use as features for classification information extracted from a direct representation of the scene (visual features), as opposed to indirect representations such as silhouettes, body parts...
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: Elektronika ir Elektrotechnika
سال: 2018
ISSN: 2029-5731,1392-1215
DOI: 10.5755/j01.eie.24.3.15290