Scalable Object Recognition Using Hierarchical Quantization with a Vocabulary Tree

An image retrieval technique employing a novel hierarchical feature/descriptor vector quantizer tool—‘vocabulary tree’, of sorts comprising hierarchically organized sets of feature vectors—that effectively partitions feature space in a hierarchical manner, creating a quantized space that is mapped to integer encoding. The computerized implementation of the new technique(s) employs subroutine components, such as: A trainer component of the tool generates a hierarchical quantizer, Q, for application/use in novel image-insertion and image-query stages. The hierarchical quantizer, Q, tool is generated by running k-means on the feature (a/k/a descriptor) space, recursively, on each of a plurality of nodes of a resulting quantization level to ‘split’ each node of each resulting quantization level. Preferably, training of the hierarchical quantizer, Q, is performed in an ‘offline’ fashion

Binomial Mitotic Segregation of MYCN-Carrying Double Minutes in Neuroblastoma Illustrates the Role of Randomness in Oncogene Amplification

BACKGROUND: Amplification of the oncogene MYCN in double minutes (DMs) is a common finding in neuroblastoma (NB). Because DMs lack centromeric sequences it has been unclear how NB cells retain and amplify extrachromosomal MYCN copies during tumour development. PRINCIPAL FINDINGS: We show that MYCN-carrying DMs in NB cells translocate from the nuclear interior to the periphery of the condensing chromatin at transition from interphase to prophase and are preferentially located adjacent to the telomere repeat sequences of the chromosomes throughout cell division. However, DM segregation was not affected by disruption of the telosome nucleoprotein complex and DMs readily migrated from human to murine chromatin in human/mouse cell hybrids, indicating that they do not bind to specific positional elements in human chromosomes. Scoring DM copy-numbers in ana/telophase cells revealed that DM segregation could be closely approximated by a binomial random distribution. Colony-forming assay demonstrated a strong growth-advantage for NB cells with high DM (MYCN) copy-numbers, compared to NB cells with lower copy-numbers. In fact, the overall distribution of DMs in growing NB cell populations could be readily reproduced by a mathematical model assuming binomial segregation at cell division combined with a proliferative advantage for cells with high DM copy-numbers. CONCLUSION: Binomial segregation at cell division explains the high degree of MYCN copy-number variability in NB. Our findings also provide a proof-of-principle for oncogene amplification through creation of genetic diversity by random events followed by Darwinian selection

An Efficient Minimal Solution for Infinitesimal Camera Motion

Given five motion vectors observed in a calibrated camera, what is the rotational and translational velocity of the camera? This problem is the infinitesimal motion analogue to the five-point relative orientation problem, which has previously been solved through the derivation of a tenth-degree polynomial and extraction of its roots. Here, we present the first efficient solution to the infinitesimal version of the problem. The solution is faster than its finite counterpart. In our experiments, we investigate over which range of motions and scene distances the infinitesimal approximation is valid and show that the infinitesimal approximation works well in applications such as camera tracking. 1

Scalable Recognition with a Vocabulary Tree

A recognition scheme that scales efficiently to a large number of objects is presented. The efficiency and quality is exhibited in a live demonstration that recognizes CD-covers from a database of 40000 images of popular music CD's. The schem

How Hard is 3-view Triangulation Really?

We present a solution for optimal triangulation in three views. The solution is guaranteed to find the optimal solution because it computes all the stationary points of the (maximum likelihood) objective function. Internally

Non-Parametric Self-Calibration

In this paper we develop a theory of non-parametric self-calibration. Recently, schemes have been devised for non-parametric laboratory calibration, but not for selfcalibration. We allow an arbitrary warp to model the intrinsic mapping, with the only restriction that the camera is central and that the intrinsic mapping has a well-defined non-singular matrix derivative at a finite number of points under study

Recent Developments on Direct Relative Orientation

This paper presents a novel version of the five-point relative orientation algorithm given in Nister (2004). The name of the algorithm arises from the fact that it can operate even on the minimal five point correspondences required for a finite number of solutions to relative orientation. For the minimal five correspondences the algorithm returns up to ten real solutions. The algorithm can also operate on many points. Like the previous version of the five-point algorithm, our method can operate correctly even in the face of critical surfaces, including planar and ruled quadric scenes. The pape

A minimal solution for relative pose with unknown focal length

Assume that we have two perspective images with known intrinsic parameters except for an unknown common focal length. It is a minimally constrained problem to find the relative orientation between the two images given six corresponding points. To this problem which to the best of our knowledge was unsolved we present an efficient solver. Through numerical experiments we demonstrate that the algorithm is correct, numerically stable and useful. The solutions are found through eigen-decomposition of a 15 15 matrix. The matrix itself is generated in closed form