Search Results - "2007 IEEE Conference on Computer Vision and Pattern Recognition"

A Benchmark for the Comparison of 3-D Motion Segmentation Algorithms by Tron, R., Vidal, R.

“…Over the past few years, several methods for segmenting a scene containing multiple rigidly moving objects have been proposed. However, most existing methods…”
Get full text

Multiple Class Segmentation Using A Unified Framework over Mean-Shift Patches by Yang, Lin, Meer, Peter, Foran, David J.

“…Object-based segmentation is a challenging topic. Most of the previous algorithms focused on segmenting a single or a small set of objects. In this paper, the…”
Get full text

Discovery of Collocation Patterns: from Visual Words to Visual Phrases by Junsong Yuan, Ying Wu, Ming Yang

“…A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a…”
Get full text

Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts by Fidler, S., Leonardis, A.

“…This paper proposes a novel approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large…”
Get full text

Learning Visual Similarity Measures for Comparing Never Seen Objects by Nowak, E., Jurie, F.

“…In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of…”
Get full text

Spatial selection for attentional visual tracking by Ming Yang, Junsong Yuan, Ying Wu

“…Long-duration tracking of general targets is quite challenging for computer vision, because in practice target may undergo large uncertainties in its visual…”
Get full text

Connecting the Out-of-Sample and Pre-Image Problems in Kernel Methods by Arias, P., Randall, G., Sapiro, G.

“…Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is…”
Get full text

Marker-less Deformable Mesh Tracking for Human Shape and Motion Capture by de Aguiar, E., Theobalt, C., Stoll, C., Seidel, H.-P.

“…We present a novel algorithm to jointly capture the motion and the dynamic shape of humans from multiple video streams without using optical markers. Instead…”
Get full text

Map-Enhanced UAV Image Sequence Registration and Synchronization of Multiple Image Sequences by Yuping Lin, Medioni, G.

“…Registering consecutive images from an airborne sensor into a mosaic is an essential tool for image analysts. Strictly local methods tend to accumulate errors,…”
Get full text

Quasi-Dense Wide Baseline Matching Using Match Propagation by Kannala, J., Brandt, S.S.

“…In this paper we propose extensions to the match propagation algorithm which is a technique for computing quasi-dense point correspondences between two views…”
Get full text

Sensor noise modeling using the Skellam distribution: Application to the color edge detection by Youngbae Hwang, Jun-Sik Kim, In-So Kweon

“…In this paper, we introduce the Skellam distribution as a sensor noise model for CCD or CMOS cameras. This is derived from the Poisson distribution of photons…”
Get full text

The Hyperbolic Geometry of Illumination-Induced Chromaticity Changes by Lenz, R., Latorre Carmona, P., Meer, P.

“…The non-negativity of color signals implies that they span a conical space with a hyperbolic geometry. We use perspective projections to separate intensity…”
Get full text

Object retrieval with large vocabularies and fast spatial matching by Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.

“…In this paper, we present a large-scale object retrieval system. The user supplies a query object by selecting a region of a query image, and the system…”
Get full text

Saliency Detection: A Spectral Residual Approach by Xiaodi Hou, Liqing Zhang

“…The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent…”
Get full text

Evaluation of Cost Functions for Stereo Matching by Hirschmuller, H., Scharstein, D.

“…Stereo correspondence methods rely on matching costs for computing the similarity of image locations. In this paper we evaluate the insensitivity of different…”
Get full text

Matching Local Self-Similarities across Images and Videos by Shechtman, E., Irani, M.

“…We present an approach for measuring similarity between visual entities (images or videos) based on matching internal self-similarities. What is correlated…”
Get full text

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition by Ranzato, M.A., Fu Jie Huang, Boureau, Y.-L., Yann LeCun

“…We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting…”
Get full text

Fisher Kernels on Visual Vocabularies for Image Categorization by Perronnin, F., Dance, C.

“…Within the field of pattern classification, the Fisher kernel is a powerful framework which combines the strengths of generative and discriminative approaches…”
Get full text

Learning Conditional Random Fields for Stereo by Scharstein, D., Pal, C.

“…State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose heuristic restrictions or priors…”
Get full text

Learning to Detect A Salient Object by Tie Liu, Jian Sun, Nan-Ning Zheng, Xiaoou Tang, Heung-Yeung Shum

“…We study visual attention by detecting a salient object in an input image. We formulate salient object detection as an image segmentation problem, where we…”
Get full text