Camera Distance Research Articles

Refocusing distance of a standard plenoptic camera.

Recent developments in computational photography enabled variation of the optical focus of a plenoptic camera after image exposure, also known as refocusing. Existing ray models in the field simplify the camera's complexity for the purpose of image and depth map enhancement, but fail to satisfyingly predict the distance to which a photograph is refocused. By treating a pair of light rays as a system of linear functions, it will be shown in this paper that its solution yields an intersection indicating the distance to a refocused object plane. Experimental work is conducted with different lenses and focus settings while comparing distance estimates with a stack of refocused photographs for which a blur metric has been devised. Quantitative assessments over a 24 m distance range suggest that predictions deviate by less than 0.35 % in comparison to an optical design software. The proposed refocusing estimator assists in predicting object distances just as in the prototyping stage of plenoptic cameras and will be an essential feature in applications demanding high precision in synthetic focus or where depth map recovery is done by analyzing a stack of refocused photographs.

A Portable Rice Disease Diagnosis Tool Basedon Bi-Level Color Image Thresholding

The rice plant is a cereal crop and staple food forpeople living in many Asian countries. Disease can lead to an underproduction of paddy-rice yield. In the past, diagnosing rice diseases required high-level skills to detect diseases accurately and was often very time consuming. Most mistakes happen due to human vision restrictions. In addition, each crop field disease has similar symptoms, making it hard to discriminate between each one. Additionally, current single thresholding methods are often not effective when separating color of lesion from the color of image background due to color information ignorance. To overcome these difficulties, we present a complete portable and real-time device for predicting rice diseases with an introduction of a bi-level thresholding method for segmenting regions of interest. The research methodology begins with camera calibration using distance versus a preset rectangular region of interest, image capturing via portable and real-time devices, image segmentation using a proposed bi-level threshold, system extraction based on image texture analysis and rice abnormality recognition via production rule method. Every captured image recognizes abnormality according to lesion shape and color. The rice abnormalities were classified into four classes including Blast Disease, Brown Spot Disease, Narrow Brown Spot Disease, and Sheath Blast Disease, while normal leaves are used as the test control. From all 120 real-time data images, only 85 data images are used for validation. Two experiments were conducted for optimal camera calibration testing via real time portable device and the proposed single threshold method testing. The experiment result shows that 20 cm is the optimal portable camera distance and that the proposed bi-level threshold achieves better accuracy (approximately 87%) compared with other state-of-the-art methods, namely the potential difference and color threshold methods (with approximately 82.4% and 54.2% accuracy, respectively).

Shot scale distribution in art films

The scale of shot, i.e. the apparent distance of the camera from the main subject of a scene, is one of the main stylistic and narrative functions of audiovisual products, conveying meaning and inducing the viewer's emotional state. The statistical distribution of different shot scales in a film may be an important identifier of an individual film, an individual author, and of various narrative and affective functions of a film. In order to understand at which level shot scale distribution (SSD) of a movie might become its fingerprint, it is necessary to produce automatic recognition of shot scale on a large movie corpus. In our work we propose an automatic framework for estimating the SSD of a movie by using inherent characteristics of shots containing information about camera distance, without the need to recover the 3D structure of the scene. In the experimental investigation, the comparison of obtained results with manual SSD annotations proves the validity of the framework. Experiments conducted on movies by Michelangelo Antonioni taken from different stylistic periods (1950---57, 1960---64, 1966---75, 1980---82) show a strong similarity in shot scale distributions within each period, thus opening interesting research lines regarding the possible aesthetic and cognitive sources of such a regularity.

Evaluation of feature point detection in high dynamic range imagery

This paper evaluates the suitability of High Dynamic Range (HDR) imaging techniques for Feature Point (FP) detection under demanding lighting conditions. The FPs are evaluated in HDR, tone mapped HDR, and traditional Low Dynamic Range (LDR) images. Eleven global and local tone mapping operators are evaluated and six widely used FP detectors are used in the experiments (Harris, Shi–Tomasi, DoG, Fast Hessian, FAST, and BRISK). The distribution and repeatability rate of FPs are studied under changes of camera viewpoint, camera distance, and scene lighting. The results of the experiments show that current FP detectors cannot cope with HDR images well. The best contemporary solution is thus tone mapping of HDR images using a local tone mapper as a pre-processing step.

Uncertainty Analysis for Emissivity Measurement at Elevated Temperatures with an Infrared Camera

The current work describes the measurement of emissivity of rock samples and black paint Pyromark 2500 within the temperature range between $$230\,^\circ $$ C and $$650\,^\circ $$ C together with its detailed uncertainty analysis. The infrared camera Optris PI450 was used to obtain the surface temperature of the samples. The described method is based on adjusting the emissivity of the rock sample until the temperature of the rock surface detected by the IR camera matches the temperature of a reference body. The reference body represented the tested rock sample partially coated with Pyromark 2500. The emissivity of the paint was previously determined with a technique described in this work: Pyromark 2500 was applied on a ceramic heater and heated up to a certain temperature that was calculated from measured electrical resistance of the ceramic heater (previously calibrated as a resistance thermometer). The emissivity measurement of rock samples is flexible concerning the type of sample, its size, position relative to the IR camera (distance, observation angle), and environmental conditions. Emissivities of Gotthard granite and Paradiso migmatite are reported, and they are in an agreement with emissivities of some granite samples from literature. The uncertainty of the rock sample emissivity reaches the value of $$10\,\%$$ and the main contribution to it is related to the electrical resistance measurement of the ceramic heater.

テンプレート照合を用いた局所特徴の射影不変性診断法

SUMMARY It is well known that points on a plane in 3D world are related to corresponding image points in a view of a moving camera by projective translation. Good image features have robust projectivity under any camera movements. In the standard performance evaluation of image processing, real captured images of a scene are used ordinarily. However, it is not enough to evaluate in detail because the variation of camera angle and distance to target objects are limited and the capturing cost is expensive. During the early stage of the image processing development, the basic performance measurement should be the most important in an easy way. We propose a projectivity diagnosis method to measure the performance of local descriptor base template matching between a template image and reference images which are created by deforming the template image. This template matching consists of a feature image point extraction and a local descriptor matching. The proposed method evaluates the positional accuracy of the extracted feature points and the matching with local descriptor. Four metrics are introduced to evaluate the projectivity of template matching. In the experiment, our proposed diagnosis method expose the projectivity of SIFT, SURF, and ORB. SIFT showed the better robustness than the others.

Non-destructive inspection of aircraft composite materials using triple IR imaging

Abstract: The wide use of composite materials in a number of industrial sectors has necessitated the development of new nondestructive inspection techniques for both manufacturing quality assurance and in-service damage testing. This paper discusses the development of a new holistic inspection system for aircraft composite materials that is composed of three thermographic cameras (operating at different wavelengths such as Near-infrared, Mid-Wave and Long-Wave) placed on the head of a robotic arm. Different setups were investigated in order to achieve optimal settings for a variety of influencing parameters including camera distance from the surface under investigation, excitation source type and power. Experiments were also conducted to define the effectiveness of each thermographic camera towards a variety of defect types. Advanced image processing algorithms were further developed and deployed to enhance the inspection capabilities of the three cameras and improve the interpretation of the collected thermal images. Future work on validating fusion and machine learning tools, their integration as well as on-site inspections has been planned.

THE EFFECT OF VARIES CAMERA CALIBRATION FIELDS ON CAMERA PARAMETERS

All photogrammetric applications need good camera parameters for mapping purpose, such as an Unmanned Aerial Vehicle (UAV) that encompassed with camera devices. Simple camera calibration is commonly used in many experiments in order to obtain the camera parameter’s value. In aerial mapping, interior camera parameters value of close-range camera calibration is used to correct the image error. However, the changes of the interior calibration parameters used need to be considered at different heights of mapping. Therefore, this research aims to contribute by analyzing of camera parameters’ changes from three heights using calibration field, and one camera calibration in the laboratory as commonly used. Camera distance heights of 15 metre, 25 metre, 55 metre, and 1.4 metre camera distance in the laboratory. The results show the changes in camera parameter’s value. Hence, value of camera calibration parameters of a camera is considered different and can change depend on the distance (height) of calibration.

Camera calibration and pose estimation from planes

Camera calibration plays a key role in every computer vision application dealing with the problems of recovering a camera's geometry with respect to a 3D world reference, making 3D measurement in a captured scene or extracting 3D data from observed objects. These problems emerge in various applications such as structure from motion, robotics, augmented reality, 3D object recognition, and Simultaneous Localization And Mapping (SLAM). Using a camera as a measuring device is becoming an important trend [1], and as a consequence the need for calibrating this instrument also becomes of prime importance. Cameras are, by nature, projective devices that map our 3D world onto a 2D image. Their prime use is to create representations (i.e., images) of an environment and its actors as pictured from a particular viewpoint at a precise moment in time. Extracting 3D data from such devices is therefore inherently difficult. The camera measures the intensity of the light emitted or reflected from a certain direction; however, the depth information is lost. The projective process also implies that, in the absence of any external reference, the scale of the observed objects is undeterminable; that is an object of a given size at a given camera distance will produce the same image as an object of twice the size seen at twice the distance. In spite of these limitations, with a good understanding of the camera geometry, 3D reconstruction can become possible under specific circumstances. In this article, we review some techniques proposed in the literature to parameterize camera metric information, also referred to as camera calibration techniques. We also illustrate the use of calibrated cameras by describing two application examples involving camera pose estimation and distance estimation.

Improvement of photogrammetric JRC data distributions based on parabolic error models

This research describes the influences of the focal length of lenses as well as camera-to-object distances that control the accuracy and precision of 3D photogrammetry models used for assessing joint roughness coefficients (JRC). A parabolic error model, which is developed by a series of photogrammetric laboratory tests, is used to improve the JRC data distributions obtained from the photogrammetry 3D models. The influences of camera-to-object distances and focal lengths on the accuracy of JRC values are investigated in laboratory conditions. A series of photogrammetry tests are performed under different conditions by varying the camera-to-object distances and the camera lens focal lengths. The camera positions are controlled on a sliding device to increase the accuracy of geo-referencing. The results suggest the allowable photographic distances for the employed photogrammetry equipment (e.g. camera and focal lengths of lenses) to estimate JRC values through comparison with the manually measured values. The root-mean-square-error (RMSE) of JRC functions, which are correlated with the camera distances and the normalized JRC values, are depicted as different size parabolic curves according to the employed focal lengths. These models successfully improve on the accuracy of the originally obtained JRC distributions.

피부 상태 추정을 위한 촬영 거리에 적응적인 모공 검출 연구

Nowadays, cameras embedded in smartphones can take high resolution photographs that can be used to analyze skin conditions without using specialized equipments. In shooting photographs with a smartphone, it is difficult to maintain a uniform shooting distance. Therefore, it is essential to adapt a skin analysis method to the shooting distance. In this paper, we focus on a pore detection algorithm that is adaptive to the camera distance. We develop a relationship model between the shooting distance and the appropriate size of the pore detection mask. In addition, we propose a method to estimate the normalized pore size (i. e. pore size at a standard shooting distance). We conducted experiments on skin images taken from different shooting distances. It was verified that the proposed method can achieve more accurate pore detection result, close to those from skin images taken at a standard shooting distance.

OPTIMASI PROSES PENGUKURAN DIMENSI DAN DEFECT UBIN KERAMIK MENGGUNAKAN PENGOLAHAN CITRA DIGITAL DAN FULL FACTORIAL DESIGN

Theinspection process of surface quality of ceramic tile could be done by using image processing technique throughthe optimization by using Center for Ceramics’s parameteron Indonesian National Standard (SNI) ISO 10545.This research will analyze from light intensities (level 300lx, 600lx, and 900lx), and camera distances (50cm, 75cmand 100cm), with three times replication using full factorial design. This research uses Matlab 2009a softwareto identify area and defect on dry spots ceramic tile’s surface. The result obtained from this research is there weresignificant influencing factors: light intensity, and camera distance, as well as the interaction of these factorstowards the error rate percentage of measuring areaand defect on ceramic tile’s surface. The smallest error ratevalue from measuring tile’s surface and diameter of dry spots with light intensity of 300lx and camera distance of50cm had been obtained the error rate value for each measurement about 0.0675% and 2.30%, with combinationof grayscale value for the error rate measurements of tile’s surface and diameter of dry spots were 0.2989 x 0.1140x R + G+0.5870 x B. Based on the correlation coefficient value between light intensity, camera distance towardsthe error rate of measuring areaand defect on tile’s surface, each of them was obtained correlation coefficient valueof camera distance with error rate had 0.518 and 0.516, which meant a strong correlation. The positive correlationcoefficient value showed a unidirectional relationship of two variables, where the rise of one variable would causethe rise of another variable and the decline of one variable would cause the decline of another variable.

Arthroscopic Skills Acquisition Tools: An Online Simulator for Arthroscopy Training

To evaluate correlations between objective performances measured by a new online arthroscopic skills acquisition tool (ASAT, in which "shape match" with inverted controls requires lifting shapes and releasing them into their corresponding silhouettes) and a validated virtual reality (VR) shoulder arthroscopy simulator (Insight Arthro VR; GMV, Madrid, Spain). Forty-nine medical students familiarized themselves with 5 ASATs. They were then assessed using a sixth ASAT (shape match with inverted controls) and 4 VR tasks (operating room, visualize, locate and palpate, and pendulum) on the VR simulator. Correlations were assessed between 11 ASAT measures and 15 VR measures using Pearson correlation coefficients. Time taken and delta distance (actual distance minus minimum distance traveled) were the most frequent and correlated ASAT measures. Time taken correlated with the VR locate-and-palpate time (r = 0.596, P < .001), visualize time (r = 0.381, P = .007), and pendulum time (r = 0.646, P < .001), whereas delta distance correlated with the locate-and-palpate camera distance (r = 0.667, P < .001), instrument distance (r = 0.664, P < .001), visualize distance (r = 0.4, P = .004), pendulum camera distance (r = 0.538, P < .001), and instrument distance (r = 0.539, P < .001). There were significant correlations between performance measures on the ASAT and a validated arthroscopic VR simulator. Arthroscopic simulators are available but are limited by their high cost and availability. ASATs may overcome these limitations by using widely available Internet-based software and basic input devices.

SU‐E‐J‐197: Investigation of Microsoft Kinect 2.0 Depth Resolution for Patient Motion Tracking

Purpose:Investigate the use of the Kinect 2.0 for patient motion tracking during radiotherapy by studying spatial and depth resolution capabilities.Methods:Using code written in C#, depth map data was abstracted from the Kinect to create an initial depth map template indicative of the initial position of an object to be compared to the depth map of the object over time. To test this process, simple setup was created in which two objects were imaged: a 40 cm × 40 cm board covered in non reflective material and a 15 cm × 26 cm textbook with a slightly reflective, glossy cover. Each object, imaged and measured separately, was placed on a movable platform with object to camera distance measured. The object was then moved a specified amount to ascertain whether the Kinect's depth camera would visualize the difference in position of the object.Results:Initial investigations have shown the Kinect depth resolution is dependent on the object to camera distance. Measurements indicate that movements as small as 1 mm can be visualized for objects as close as 50 cm away. This depth resolution decreases linearly with object to camera distance. At 4 m, the depth resolution had decreased to observe a minimum movement of 1 cm.Conclusion:The improved resolution and advanced hardware of the Kinect 2.0 allows for increase of depth resolution over the Kinect 1.0. Although obvious that the depth resolution should decrease with increasing distance from an object given the decrease in number of pixels representing said object, the depth resolution at large distances indicates its usefulness in a clinical setting.

Perancangan Aplikasi Multimedia Untuk Pembelajaran Gerbang Logika Menggunakan Augmented Reality

As the rapid development of technology is also growing media that is used as a method of learning in education. One of them to learning logic states, in addition to reading the book at this time there has a new learning method that is more pronounced in 3 dimensions to increase understanding in learning the logic gates using Augmented Reality. Steps design multimedia for learning the logic gates begins with a literature study, data collection, analysis and system design and then implementation and testing the system. Testing methods using a black-box, which includes testing functionality testing camera angles and distances to the markers as well as testing the light intensity. The result of the design this application shows that for angle of 30 0 with a distance of 30 cm – 40 cm, angle of 45 0 with a distance of 40 cm – 70 cm and angle of 60 0 with a distance of 50 cm – 90 cm and light intensity 4 lx – 19 lx is a good composition can display the object 3 dimensions.

Human Action Recognition based on Spectral Domain Features

Abstract In this paper, we propose a novel approach towards human action recognition using spectral domain feature extraction. Action representations can be considered as image templates, which can be useful for understanding various actions or gestures as well as for recognition and analysis. An action recognition scheme is developed based on extracting spectral features from the frames of a video sequence using the two-dimensional discrete Fourier transform (2D-DFT). The proposed spectral feature selection algorithm offers the advantage of very low feature dimensionality and thus lower computational cost. We show that using frequency domain features enhances the distinguishability of different actions, resulting in high within-class compactness and between-class separability of the extracted features, while certain undesirable phenomena, such as camera movement and change in camera distance, are less severe in the frequency domain. Principal component analysis is performed to further reduce the dimensionality of the feature space. Experimental results on a benchmark action recognition database confirm that our proposed method offers not only computational savings but also a high degree of accuracy.

Optimization of Coral Video Transect Technique for Coral Reef Survey: Comparison with Intercept Transect Technique

Variety in video sampling protocol for coral reef survey worldwide has prompted this study to create an optimized protocol for Coral Video Transect (CVT) technique for coral reef survey in Malaysia. The effect of different vertical distance of the camera above the substrate during video recording, number of frames and points analyzed as well as time spent during field and analysis were examined to determine an optimal protocol for CVT technique at different coral reef conditions in Malaysia’s water. Video recording taken at 0.5 m camera distance was selected as optimize vertical distance above the substrate as it can identify more benthic categories than 1.0 m with lesser time taken as well as frames extracted than 0.2 m. Respectively, 80% of total frames extracted from 20 m transect and analyzed with 50 points per frames were chosen as an optimized sample size for its ability to precisely estimate percent cover and accurately identify benthic categories. This optimized protocol was then compared with Line Intercept Transect (LIT) method. No clear difference in estimating percentage cover of major benthic categories between CVT and LIT method, but CVT recorded a significantly higher number of benthic categories with lesser time spent during field survey as compared to LIT method. This implied that the optimize CVT method can precisely estimate percent cover and accurately identify benthic categories in coral communities and are thus more suitable for scientific research and management purposes than LIT method. Other advantages of using this technique are by providing a permanent data that can be reassessed later on, lesser field time and wider survey area. Overall, this study showed that CVT technique is an acceptable alternative method of coral reef survey in Malaysia.

Estimating density of secretive terrestrial birds (Siamese Fireback) in pristine and degraded forest using camera traps and distance sampling

Tropical Asian Galliformes are secretive and difficult to survey. Many of these species are considered “at risk” due to habitat degradation although reliable density estimates are lacking. Using camera trapping and distance sampling data collected on the Siamese Fireback (Lophura diardi) in northeastern Thailand, we compared density estimates for pristine and degraded lowland forest. Density was poorly estimated using distance sampling, likely due to small sample size arising from poor visibility in dense vegetation and bird’s sensitivity to observers. We analysed camera trap data using both count-based and presence/absence-based methods. Those density estimates had narrower confidence intervals than those obtained using distance sampling. Estimated density was higher in dry evergreen forest (5.6 birds km−2), than in old forest plantations (0.2 birds km−2), perhaps because dense forest habitats provide Firebacks with more resources and refuge from predation. Our results suggest that camera trap data can be used for estimating density of cryptic terrestrial bird species inhabiting tropical forest that lack unique identification markings. However, this technique requires that the effective sampling area is known and thus requires knowledge of the animal home range size.

Effect of Source to Camera Distance and Count Rate on Intrinsic Uniformity of SPECT Gamma Camera

In this research, the excellent parameter for regular Quality Control (QC) testing of intrinsic uniformity for dual-head Single Photon Emission Computed Tomography (SPECT) gamma camera is determined. The integral and differential intrinsic uniformity tests for both Useful Field Of View (UFOV) and Centre Field Of View (CFOV) were done by insertion a point-source of 99mTc in front of the detectors with detached collimators to measure the effect of source to camera distance and a count rate on intrinsic uniformity. The result reveals that the best intrinsic uniformity image is obtained at source-to-camera distance of 3 m and a count rate between 16 and 60 M.

Detection and matching of iris region in images taken in Unfavorable conditions like light, camera distance etc. For making iris recognition systems more effective

Detection and matching of iris region in images taken in Unfavorable conditions like light, camera distance etc. For making iris recognition systems more effective