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Action recognition by dense trajectories
This work introduces a novel descriptor based on motion boundary histograms, which is robust to camera motion and consistently outperforms other state-of-the-art descriptors, in particular in uncontrolled realistic videos.
Dense Trajectories and Motion Boundary Descriptors for Action Recognition
- Heng Wang, Alexander Kläser, C. Schmid, Cheng-Lin Liu
- Computer ScienceInternational Journal of Computer Vision
- 6 March 2013
The MBH descriptor shows to consistently outperform other state-of-the-art descriptors, in particular on real-world videos that contain a significant amount of camera motion.
ICDAR2017 Robust Reading Challenge on Multi-Lingual Scene Text Detection and Script Identification - RRC-MLT
- Nibal Nayef, Fei Yin, J. Ogier
- Computer Science14th IAPR International Conference on Document…
- 1 November 2017
This paper presents the dataset, the tasks and the findings of this RRC-MLT challenge, which aims at assessing the ability of state-of-the-art methods to detect Multi-Lingual Text in scene images, such as in contents gathered from the Internet media and in modern cities where multiple cultures live and communicate together.
CASIA Online and Offline Chinese Handwriting Databases
- Cheng-Lin Liu, Fei Yin, Da-Han Wang, Qiu-Feng Wang
- Computer ScienceInternational Conference on Document Analysis and…
- 18 September 2011
A pair of online and offline Chinese handwriting databases, containing samples of isolated characters and handwritten texts, are introduced, which can be used for the research of various handwritten document analysis tasks.
ICDAR 2013 Chinese Handwriting Recognition Competition
- Fei Yin, Qiu-Feng Wang, Xu-Yao Zhang, Cheng-Lin Liu
- Computer Science12th International Conference on Document…
- 25 August 2013
This paper describes the Chinese handwriting recognition competition held at the 12th International Conference on Document Analysis and Recognition (ICDAR 2013), and reports the best results (correct rates) for classification on extracted features, offline character recognition, and online/offline handwritten text recognition.
A Hybrid Approach to Detect and Localize Texts in Natural Scene Images
- Yi-Feng Pan, Xinwen Hou, Cheng-Lin Liu
- Computer ScienceIEEE Transactions on Image Processing
- 1 March 2011
A hybrid approach to robustly detect and localize texts in natural scene images using a text region detector, a conditional random field model, and a learning-based energy minimization method are presented.
Deep Direct Regression for Multi-oriented Scene Text Detection
- Wenhao He, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu
- Computer ScienceIEEE International Conference on Computer Vision…
- 24 March 2017
A deep direct regression based method for multi-oriented scene text detection that achieves the F-measure of 81%, which is a new state-of-the-art and significantly outperforms previous approaches.
'Online recognition of Chinese characters: the state-of-the-art
- Cheng-Lin Liu, Stefan Jäger, M. Nakagawa
- Computer ScienceIEEE Transactions on Pattern Analysis and Machine…
This paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s, in terms of pattern representation, character classification, learning/adaptation, and contextual processing.
Consensus of Multi-Agent Systems With Diverse Input and Communication Delays
- Yu-Ping Tian, Cheng-Lin Liu
- Mathematics, Computer ScienceIEEE Transactions on Automatic Control
- 7 October 2008
The consensus problem for multi-agent systems with input and communication delays is studied based on the frequency-domain analysis. Two decentralized consensus conditions are obtained, one of which…
Retargeted Least Squares Regression Algorithm
- Xu-Yao Zhang, Lingfeng Wang, Shiming Xiang, Cheng-Lin Liu
- Computer ScienceIEEE Transactions on Neural Networks and Learning…
- 1 September 2015
This brief presents a framework of retargeted least squares regression (ReLSR) for multicategory classification. The core idea is to directly learn the regression targets from data other than using…