An object recognition system has been developed that uses a new class of local image features. The features are invariant to scaling, translation, and rotation, partially illumination changes affine or 3D projection. These share similar properties with neurons in inferior temporal cortex used for primate vision. Features efficiently detected through staged filtering approach identifies stable points scale space. Image keys created allow geometric deformations by representing blurred...

We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences. In common with recent work [10, 14, 16], we use end-to-end approach view synthesis as supervisory signal. contrast to previous work, our method is completely unsupervised, requiring only sequences training. Our uses single-view multiview pose networks, a loss based on warping nearby views target using computed pose. The networks are thus coupled by...

For many computer vision problems, the most time consuming component consists of nearest neighbor matching in high-dimensional spaces.There are no known exact algorithms for solving these problems that faster than linear search.Approximate to provide large speedups with only minor loss accuracy, but such have been published minimal guidance on selecting an algorithm and its parameters any given problem.In this paper, we describe a system answers question, "What is fastest approximate...

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of algorithms consists finding nearest neighbor matches to high dimensional vectors that represent data. We propose new approximate matching evaluate compare them with previous algorithms. features, we find two be efficient: randomized k-d forest a algorithm proposed in this paper, priority search k-means tree. also binary features by...

Shape indexing is a way of making rapid associations between features detected in an image and object models that could have produced them. When model databases are large, the use high-dimensional critical, due to improved level discrimination they can provide. Unfortunately, finding nearest neighbour query point rapidly becomes inefficient as dimensionality feature space increases. Past methods used hash tables for hypothesis recovery, but only low-dimensional situations. In this paper we...

Model-based recognition and motion tracking depend upon the ability to solve for projection model parameters that will best fit a 3-D matching 2-D image features. The author extends current methods of parameter solving handle objects with arbitrary curved surfaces any number internal representing articulation, variable dimensions, or surface deformations. Numerical stabilization are developed take account inherent inaccuracies in measurements allow useful solutions be determined even when...

A key component of a mobile robot system is the ability to localize itself accurately and, simultaneously, build map environment. Most existing algorithms are based on laser range finders, sonar sensors or artificial landmarks. In this paper, we describe vision-based localization and mapping algorithm, which uses scale-invariant image features as natural landmarks in unmodified environments. The invariance these translation, scaling rotation makes them suitable for building. With our...

The natriuretic peptides are hormones that can stimulate natriuretic, diuretic, and vasorelaxant activity in vivo, presumably through the activation of two known cell surface receptor guanylyl cyclases (ANPR-A ANPR-B). Although atrial peptide (ANP) and, to a lesser extent, brain (BNP) efficient activators ANPR-A cyclase, neither hormone significantly ANPR-B. A member this family, C-type (CNP), potently selectively activated human ANPR-B cyclase. CNP does not increase guanosine...

This paper approaches the problem of ¯nding correspondences between images in which there are large changes viewpoint, scale and illumi- nation. Recent work has shown that scale-space `interest points' may be found with good repeatability spite such changes. Further- more, high entropy surrounding image regions means local descriptors highly discriminative for matching. For descrip- tors at interest points to robustly matched images, they must as far possible invariant imaging process. In...

Human vision is able to immediately recognize novel visual categories after seeing just one or a few training examples. We describe how add similar capability ConvNet classifiers by directly setting the final layer weights from examples during low-shot learning. call this process weight imprinting as it sets for new category based on an appropriately scaled copy of embedding activations that example. The provides valuable complement with stochastic gradient descent, immediate good...

We have previously developed a mobile robot system which uses scale-invariant visual landmarks to localize and simultaneously build three-dimensional (3-D) maps of unmodified environments. In this paper, we examine global localization, where the localizes itself globally, without any prior location estimate. This is achieved by matching distinctive in current frame database map. A Hough transform approach RANSAC for localization are compared, showing that much more efficient specific...

There have been important recent advances in object recognition through the matching of invariant local image features. However, existing approaches are based on to individual training images. This paper presents a method for combining multiple images 3D into single model representation. provides objects from any viewpoint, generalization models non-rigid changes, and improved robustness combination features acquired under range imaging conditions. The decision whether cluster an view...

A key component of a mobile robot system is the ability to localize itself accurately and build map environment simultaneously. In this paper, vision-based localization mapping algorithm described which uses scale-invariant image features as landmarks in unmodified dynamic environments. These 3D are localized ego-motion estimated by matching them, taking into account feature viewpoint variation. With our Triclops stereo vision system, experiments show that these robustly matched between...

We apply a biologically inspired model of visual object recognition to the multiclass categorization problem. Our modifies that Serre, Wolf, and Poggio. As in work, we first Gabor filters at all positions scales; feature complexity position/scale invariance are then built up by alternating template matching max pooling operations. refine approach several plausible ways, using simple versions sparsification lateral inhibition. demonstrate value retaining some position scale information above...