Scene Video Text Tracking With Graph Matching
نویسندگان
چکیده
منابع مشابه
Scene Text Area Detection from Video
Text detection from videos is a well known research area. Especially the detection of static superimposed text such as captions has been researched successfully, but makes many assumptions that question the applicability of those algorithms for moving scene text. In this dissertation, I propose a scene text area detection approach that includes a simple key frame extraction, feature extraction,...
متن کاملVideo tracking using block matching
A tracking algorithm that predicts the object contour using motion vector information is proposed in this paper. Tracking is achieved by predicting the object boundary using motion vectors, followed by contour update, using occlusionsldisocclusion detection. An adaptive block-based approach has been used for estimating motion between frames. An efficient modulation scheme is used to control the...
متن کاملAutomatic Text Detection and Tracking in Digital Video Automatic Text Detection and Tracking in Digital Video
Text which either appears in a scene or is graphically added to video can provide an important supplemental source of index information as well as clues for decoding the video's structure and for classiication. In this paper we present algorithms for detecting and tracking text components that appear within digital video frames. Our system implements a scale-space feature extractor that feeds a...
متن کاملText-independent speaker recognition using graph matching
Technical mismatches between the training and matching conditions adversely affect the performance of a speaker recognition system. In this paper, we present a matching scheme which is invariant to feature rotation, translation and uniform scaling. The proposed approach uses a neighborhood graph to represent the global shape of the feature distribution. The reference and test graphs are aligned...
متن کاملMulti-Object Tracking Using Dynamical Graph Matching
We describe a tracking algorithm to address the interactions among objects, and to track them individually and confidently via a static camera. It is achieved by constructing an invariant bipartite graph to model the dynamics of the tracking process, of which the nodes are classified into objects and profiles. The best match of the graph corresponds to an optimal assignment for resolving the id...
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 Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2797181