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» Segmentation as Selective Search for Object Recognition
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ICCV
2011
IEEE
12 years 9 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
EMMCVPR
2007
Springer
14 years 4 months ago
Compositional Object Recognition, Segmentation, and Tracking in Video
Abstract. The complexity of visual representations is substantially limited by the compositional nature of our visual world which, therefore, renders learning structured object mod...
Björn Ommer, Joachim M. Buhmann
GBRPR
2009
Springer
14 years 4 months ago
An Irregular Pyramid for Multi-scale Analysis of Objects and Their Parts
We present an irregular image pyramid which is derived from multi-scale analysis of segmented watershed regions. Our framework is based on the development of regions in the Gaussia...
Martin Drauschke
ICDAR
2011
IEEE
12 years 9 months ago
Trie-Lexicon-Driven Recognition for On-line Handwritten Japanese Disease Names Using a Time-Synchronous Method
— This paper describes a lexicon-driven approach to on-line handwritten Japanese disease name recognition using a time-synchronous method. A trie lexicon is constructed from a di...
Bilan Zhu, Masaki Nakagawa
ACIVS
2006
Springer
14 years 3 months ago
A Comparison of Nearest Neighbor Search Algorithms for Generic Object Recognition
The nearest neighbor (NN) classifier is well suited for generic object recognition. However, it requires storing the complete training data, and classification time is linear in ...
Ferid Bajramovic, Frank Mattern, Nicholas Butko, J...