112665
Simple and efficient method of calibrating a motorized zoom lens
Abstract In this work, three servo motors are used to independently control the aperture, zoom, and focus of our zoom lens. Our goal is to calibrate, efficiently, the camera parameters for all the possible configurations of lens settings. We use a calibration object suitable for zoom lens calibration to deal with the defocusing problem. Instead of calibrating the zoom lens with respect to the three lens settings simultaneously, we perform the monofocal camera calibration, adaptively, over the ranges of the zoom and focus settings while fixing the aperture setting at a preset value. Bilinear interpolation is used to provide the values of the camera parameters for those lens settings where no observations are taken. The adaptive strategy requires the monofocal camera calibration only for the lens settings where the interpolated camera parameters are not accurate enough, and is hence referred to as the calibration-on-demand method. Our experiments show that the proposed calibration-on-demand method can provide accurate camera parameters for all the lens settings of a motorized zoom lens, even though the camera calibration is performed only for a few sampled lens settings.
7506034
Fast Algorithm for Nearest Neighbor Search Based on a Lower Bound Tree
This paper presents a novel algorithm for fast nearest neighbor search. At the preprocessing stage, the proposed algorithm constructs a lower bound tree by agglomeratively clustering the sample points in the database. Calculation of the distance between the query and the sample points can be avoided ifthe lower bound of the distance is already larger than the minimum distance. The search process can thus be accelerated because the computational cost of the lower bound, which can be calculated by using the internal node of the lower bound tree, is less than that of the distance. To reduce the number of the lower bounds actually calculated, the winner-update search strategy is used for traversing the tree. Moreover; the query and the sample points can be transformed for further efficiency improvement. Our experiments show that the proposed algorithm can greatly speed up the nearest neighbor search process. When applying to the real database used in Nayar’s object recognition system, the proposed algorithm is about one thousand times faster than the exhaustive search.
16787369
Fast block matching algorithm based on the winner-update strategy
Block matching is a widely used method for stereo vision, visual tracking, and video compression. Many fast algorithms for block matching have been proposed in the past, but most of them do not guarantee that the match found is the globally optimal match in a search range. This paper presents a new fast algorithm based on the winner-update strategy which utilizes an ascending lower bound list of the matching error to determine the temporary winner. Two lower bound lists derived by using partial distance and by using Minkowski's inequality are described. The basic idea of the winner-update strategy is to avoid, at each search position, the costly computation of the matching error when there exists a lower bound larger than the global minimum matching error. The proposed algorithm can significantly speed up the computation of the block matching because: 1) computational cost of the lower bound we use is less than that of the matching error itself; 2) an element in the ascending lower bound list will be calculated only when its preceding element has already been smaller than the minimum matching error computed so far; 3) for many search positions, only the first several lower bounds in the list need to be calculated. Our experiments have shown that, when applying to motion vector estimation for several widely-used test videos, 92% to 98% of operations can be saved while still guaranteeing the global optimality. Moreover, the proposed algorithm can be easily modified either to meet the limited time requirement or to provide an ordered list of best candidate matches. Our source codes of the proposed algorithm are available at http://smart.iis.sinica.edu.tw/html/winup.html.
14540904
Camera calibration with a motorized zoom lens
This paper presents a simple and efficient method of calibrating the intrinsic camera parameters for all the lens settings of a motorized zoom lens. We fix the aperture setting and perform the camera calibration, adaptively, over the ranges of the room and focus settings. Bilinear interpolation is used to provide the values of the intrinsic camera parameters for those lens settings where no observations are taken. Our experiments show that the proposed method can provide accurate intrinsic camera parameters for all the lens settings, even though camera calibration is performed only for a small number of sampled lens settings. A calibration object suitable for zoom lens calibration is also presented.
2968797
Ego-motion estimation using optical flow fields observed from multiple cameras
In this paper, we consider a multi-camera vision system mounted on a moving object in a static three-dimensional environment. By using the motion flow fields seen by all of the cameras, an algorithm which does not need to solve the point-correspondence problem among the cameras is proposed to estimate the 3D ego-motion parameters of the moving object. Our experiments have shown that using multiple optical flow fields obtained from different cameras can be very helpful for ego-motion estimation.
14744012
Winner-update algorithm for nearest neighbor search
This paper presents an algorithm, called the winner-update algorithm, for accelerating the nearest neighbor search. By constructing a hierarchical structure for each feature point in the l/sub p/ metric space, this algorithm can save a large amount of computation at the expense of moderate preprocessing and twice the memory storage. Given a query point, the cost for computing the distances from this point to all the sample points can be reduced by using a lower bound list of the distance established from Minkowski's inequality. Our experiments have shown that the proposed algorithm can save a large amount of computation, especially when the distance between the query point and its nearest neighbor is relatively small. With slight modification, the winner-update algorithm can also speed up the search for k nearest neighbors, neighbors within a specified distance threshold, and neighbors close to the nearest neighbor.
669399
Camera Calibration: a USU Implementation
The task of camera calibration is to estimate the intrinsic and extrinsic parameters of a camera model. Though there are some restricted techniques to infer the 3-D information about the scene from uncalibrated cameras, effective camera calibration procedures will open up the possibility of using a wide range of existing algorithms for 3-D reconstruction and recognition. The applications of camera calibration include vision-based metrology, robust visual platooning and visual docking of mobile robots where the depth information is important.
18628154
A Family of Simplified Geometric Distortion Models for Camera Calibration
The commonly used radial distortion model for camera calibration is in fact an assumption or a restriction. In practice, camera distortion could happen in a general geometrical manner that is not limited to the radial sense. This paper proposes a simplified geometrical distortion modeling method by using two different radial distortion functions in the two image axes. A family of simplified geometric distortion models is proposed, which are either simple polynomials or the rational functions of polynomials. Analytical geometric undistortion is possible using two of the distortion functions discussed in this paper and their performance can be improved by applying a piecewise fitting idea. Our experimental results show that the geometrical distortion models always perform better than their radial distortion counterparts. Furthermore, the proposed geometric modeling method is more appropriate for cameras whose distortion is not perfectly radially symmetric around the center of distortion.
18836133
On the epigenetic regulation of the human reelin promoter
Reln mRNA and protein levels are reduced by approximately 50% in various cortical structures of post-mortem brain from patients diagnosed with schizophrenia or bipolar illness with psychosis. To study mechanisms responsible for this down-regulation, we have analyzed the promoter of the human reelin gene. We show that the reelin promoter directs expression of a reporter construct in multiple human cell types: neuroblastoma cells (SHSY5Y), neuronal precursor cells (NT2), differentiated neurons (hNT) and hepatoma cells (HepG2). Deletion constructs confirmed the presence of multiple elements regulating Reln expression, although the promoter activity is promiscuous, i.e. activity did not correlate with expression of the endogenous gene as reflected in terms of reelin mRNA levels. Co-transfection of the -514 bp human reelin promoter with either Sp1 or Tbr1 demonstrated that these transcription factors activate reporter expression by 6- and 8.5-fold, respectively. Within 400 bp of the RNA start site there are 100 potential CpG targets for DNA methylation. Retinoic acid (RA)-induced differentiation of NT2 cells to hNT neurons was accompanied by increased reelin expression and by the appearance of three DNase I hypersensitive sites 5' to the RNA start site. RA-induced differentiation was also associated with demethylation of the reelin promoter. To test if methylation silenced reelin expression, we methylated the promoter in vitro prior to transfection. In addition, we treated NT2 cells with the methylation inhibitor aza-2'-deoxycytidine and observed a 60-fold increase in reelin mRNA levels. The histone deacetylase inhibitors trichostatin A (TSA) and valproic acid also induced expression of the endogenous reelin promoter, although TSA was considerably more potent. These findings indicate that one determinant responsible for regulating reelin expression is the methylation status of the promoter. Our data also raise the interesting possibility that the down-regulation of reelin expression documented in psychiatric patients might be the consequence of inappropriate promoter hypermethylation.
32363
Optimal cDNA microarray design using expressed sequence tags for organisms with limited genomic information
BackgroundExpression microarrays are increasingly used to characterize environmental responses and host-parasite interactions for many different organisms. Probe selection for cDNA microarrays using expressed sequence tags (ESTs) is challenging due to high sequence redundancy and potential cross-hybridization between paralogous genes. In organisms with limited genomic information, like marine organisms, this challenge is even greater due to annotation uncertainty. No general tool is available for cDNA microarray probe selection for these organisms. Therefore, the goal of the design procedure described here is to select a subset of ESTs that will minimize sequence redundancy and characterize potential cross-hybridization while providing functionally representative probes.ResultsSequence similarity between ESTs, quantified by the E-value of pair-wise alignment, was used as a surrogate for expected hybridization between corresponding sequences. Using this value as a measure of dissimilarity, sequence redundancy reduction was performed by hierarchical cluster analyses. The choice of how many microarray probes to retain was made based on an index developed for this research: a sequence diversity index (SDI) within a sequence diversity plot (SDP). This index tracked the decreasing within-cluster sequence diversity as the number of clusters increased. For a given stage in the agglomeration procedure, the EST having the highest similarity to all the other sequences within each cluster, the centroid EST, was selected as a microarray probe. A small dataset of ESTs from Atlantic white shrimp (Litopenaeus setiferus) was used to test this algorithm so that the detailed results could be examined. The functional representative level of the selected probes was quantified using Gene Ontology (GO) annotations.ConclusionsFor organisms with limited genomic information, combining hierarchical clustering methods to analyze ESTs can yield an optimal cDNA microarray design. If biomarker discovery is the goal of the microarray experiments, the average linkage method is more effective, while single linkage is more suitable if identification of physiological mechanisms is more of interest. This general design procedure is not limited to designing single-species cDNA microarrays for marine organisms, and it can equally be applied to multiple-species microarrays of any organisms with limited genomic information.
6471646
Multicue HMM-UKF for real-time contour tracking
We propose an HMM model for contour detection based on multiple visual cues in spatial domain and improve it by joint probabilistic matching to reduce background clutter. It is further integrated with unscented Kalman filter to exploit object dynamics in nonlinear systems for robust contour tracking