Search Results - "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition"

A unified framework for interactive image segmentation via Fisher rules by Luo, Lingkun, Wang, Xiaofang, Hu, Shiqiang, Hu, Xing, Zhang, Huanlong, Liu, Yaohua, Zhang, James

“…Interactive image segmentation has been an active research topic in image processing and computer graphics. One of its appealing advantage is the optimization…”
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Auto-correct-integrated trackers with and without memory of first frames by Sekhavati, Ali, Eghbal, Najmeh

“…Visual short-term tracking in a long sequence of images with a lot of pose variations, target deformations and different types of occlusion is one of the…”
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SUN database: Large-scale scene recognition from abbey to zoo by Jianxiong Xiao, Hays, J, Ehinger, K A, Oliva, A, Torralba, A

“…Scene categorization is a fundamental problem in computer vision. However, scene understanding research has been constrained by the limited scope of…”
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Deconvolutional networks by Zeiler, M D, Krishnan, D, Taylor, G W, Fergus, R

“…Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially…”
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Anomaly detection in crowded scenes by Mahadevan, Vijay, Weixin Li, Bhalodia, Viral, Vasconcelos, Nuno

“…A novel framework for anomaly detection in crowded scenes is presented. Three properties are identified as important for the design of a localized video…”
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Secrets of optical flow estimation and their principles by Deqing Sun, Roth, S, Black, M J

“…The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical…”
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Locality-constrained Linear Coding for image classification by Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Huang, T, Yihong Gong

“…The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper…”
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Aggregating local descriptors into a compact image representation by Jégou, H, Douze, M, Schmid, C, Pérez, P

“…We address the problem of image search on a very large scale, where three constraints have to be considered jointly: the accuracy of the search, its…”
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Visual tracking decomposition by Junseok Kwon, Kyoung Mu Lee

“…We propose a novel tracking algorithm that can work robustly in a challenging scenario such that several kinds of appearance and motion changes of an object…”
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Visual object tracking using adaptive correlation filters by Bolme, David S, Beveridge, J Ross, Draper, Bruce A, Yui Man Lui

“…Although not commonly used, correlation filters can track complex objects through rotations, occlusions and other distractions at over 20 times the rate of…”
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Learning mid-level features for recognition by Boureau, Y-Lan, Bach, Francis, LeCun, Yann, Ponce, Jean

“…Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer…”
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Person re-identification by symmetry-driven accumulation of local features by Farenzena, M, Bazzani, L, Perina, A, Murino, V, Cristani, M

“…In this paper, we present an appearance-based method for person re-identification. It consists in the extraction of features that model three complementary…”
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Discriminative K-SVD for dictionary learning in face recognition by Qiang Zhang, Baoxin Li

“…In a sparse-representation-based face recognition scheme, the desired dictionary should have good representational power (i.e., being able to span the subspace…”
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Model globally, match locally: Efficient and robust 3D object recognition by Drost, B, Ulrich, M, Navab, N, Ilic, S

“…This paper addresses the problem of recognizing free-form 3D objects in point clouds. Compared to traditional approaches based on point descriptors, which…”
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Classification and clustering via dictionary learning with structured incoherence and shared features by Ramirez, I, Sprechmann, P, Sapiro, G

“…A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that…”
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P-N learning: Bootstrapping binary classifiers by structural constraints by Kalal, Z, Matas, J, Mikolajczyk, K

“…This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are…”
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Large-scale image retrieval with compressed Fisher vectors by Perronnin, F, Yan Liu, Sánchez, J, Poirier, H

“…The problem of large-scale image search has been traditionally addressed with the bag-of-visual-words (BOV). In this article, we propose to use as an…”
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Context-aware saliency detection by Goferman, Stas, Zelnik-Manor, Lihi, Tal, Ayellet

“…We propose a new type of saliency - context-aware saliency - which aims at detecting the image regions that represent the scene. This definition differs from…”
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Detecting text in natural scenes with stroke width transform by Epshtein, B, Ofek, E, Wexler, Y

“…We present a novel image operator that seeks to find the value of stroke width for each image pixel, and demonstrate its use on the task of text detection in…”
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Semi-supervised hashing for scalable image retrieval by Jun Wang, Kumar, Sanjiv, Shih-Fu Chang

“…Large scale image search has recently attracted considerable attention due to easy availability of huge amounts of data. Several hashing methods have been…”
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