Titlebook: Computer Vision - ACCV 2014 Workshops; Singapore, Singapore C.V. Jawahar,Shiguang Shan Conference proceedings 2015 Springer International P

Limousine

Performance Improvement of Dot-Matrix Character Recognition by Variation Model Based Learningis promising for reduction of cost and labor required for quality control of products. Although dot-matrix characters are constructed by specific dot patterns, variation of character appearance due to three-dimensional rotation of printing surface, bleeding of ink and missing parts of character is n

Excise

Scene Text Recognition: No Country for Old?Men?ppears among the clutter of the scene. However, recent research demonstrates that a conventional shape-based OCR engine would be able to produce competitive results in the end-to-end scene text recognition task when provided with a conveniently preprocessed image. In this paper we confirm this findi

amorphous

A Machine Learning Approach to Hypothesis Decoding in Scene Text Recognitionit becomes a new source of textual data for standard Natural Language Processing tasks and poses new problems because of the specific nature of Scene Text. In this paper, we learn a string hypotheses decoding procedure in an STR pipeline using structured prediction methods that proved to be useful i

一加就噴出

Perspective Scene Text Recognition with Feature Compression and Rankinga bag-of-words approach, in which the rotation-invariant circular Fourier-HOG features are densely extracted from an individual character and compressed into middle level features. Then we train a set of two-class linear Support Vector Machines in a one-vs-all schema to rank the compressed features

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Albumin

Debugging Object Tracking Results by a Recommender System with Correction Propagationmount of cells over months in microscopy image sequences. Meanwhile, manually debugging (verifying and correcting) tracking results object-by-object and frame-by-frame in thousands of frames is too tedious. In this paper, we propose a novel scheme to debug automated object tracking results with huma

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Conference proceedings 2015l Workshop on Video Segmentation in Computer Vision, the Workshop: My Car Has Eyes: Intelligent Vehicle with Vision Technology, the Third Workshop on E-Heritage, and the Workshop on Computer Vision for Affective Computing. LNCS 9010 contains the papers selected for the Workshop on Feature and Simila

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