Multi Camera Research Articles

Features of Organization of Work of Film Crew (Stage-director, Operator, Sound Producer and Commentator) are at Creation of Sporting Reporting

Research aim is to find out the features of direction of multi camera survey at creation of the sporting reporting and organization of work of film crew (stage-director, operator, sound producer and commentator). Research methodology is based on scientific methods. They are the analysis (successive exposition of investigational and appraised theoretical and practical material); to the synthesis (to exposition of inferencing in relation to the done research of problem); logical method (for development of the existent theoretical presentations obtained on the basis of working and walkthrough of materials of this research); comparative (used for research of foreign and home theoretical and practical sources from the theme of research) and others like that. The scientific novelty of the obtained results consists in certain functional features, the basic aesthetic and technical requirements to the film crew at the multi camera survey of sporting events and creation of the sporting reporting. Certainly, that a stage-director, operators, sound producer, commentators, producers, must: to know the rules of game of every concrete type of sport, competition from that filmed; to have professional knowledge, abilities, skill, experience and mutual understanding in a creative group; to work on a general result and maximally to realize the previous creative intentions. Conclusions . The analysis of feature of organization of work of film crew (stage-director, operator, sound producer and commentator) at creation of the sporting reporting gives an opportunity to come to the conclusion, that a collectivity and harmony of work at transference on the screen of sporting event and creation of the sporting reporting have a decision value. Every operator and sound producer must exactly know a previous stage-director score and own information about the general task of survey. Not only every kind but also different places of surveys need individual approach from a creative group. A survey is divided by a stage-director between operators for plans. A stage-director and operators must operate in accordance with a situation that is folded during competitions, that gives possibility to improvisation in the construction of composition, which depends on the nascent «staging». A quality voice row is provided by sound producer and microphonic operators. The task of sound producer consists not only in the transmission of original noises and voice of commentator in ether but also to their distribution in ether. It should be noted and highly responsible role of commentator, that supports an image a word and actively influences on perception of spectator, constantly controls spectator attention with the aim of emotional fascination of spectator a process that takes place.

DEVELOPMENT OF A MULTI CAMERA CALIBRATION FOR AN ANALYSIS AND MANIPULATION SYSTEM OF BIOLOGICAL SAMPLES IN PETRI DISHES

Abstract. Cameras can provide accurate 3D positioning for a robotic system. Calibration of interior orientation as well as the relative orientation when using multiple cameras is a necessary step. Integration of the automatic calibration process into the robot system is useful to provide a simple system for the user. The paper presents a method for calibrating a multi camera system using the open source Ceres solver and compares it to a commercial software. The motivation is a measurement system for laboratory automation where biological samples in Petri dishes will be manipulated with different tools. For this application we will examine the camera setup, show first results of the calibration and the possible accuracy. Lastly we will draw conclusions for the final system prototype and necessary improvements to be implemented in order to provide accurate measurements.

Multi Target Tracking Access with Data Association in Distributed Camera Networks

Data Association in Distributed Camera Network is a new method to analyse the large volume of video information in camera networking. It is an important step in multi camera multi target tracking. Distributed processing is a new paradigm to analyse the videos in camera network and each camera acts on its own and all cameras cooperatively work together to achieve a common goal, In this paper, we have addresses the problem of Distributed Data Association(DDA) to obtain the feet position of the object. These positions are shared with its immediate neighbours and find local matches using homography. By propagating these local matches across the network in order to obtain the global associations. In this proposed method DDA is less complex and improves the high accuracy compared to the centralized methods (STSPIE, EMTIC, JPDAEKCF, CSPIF, and CEIF).

A review of the Multiple Object Detection, Tracking and Recognition in Video Surveillance Systems using different approaches

Moving item location in any video scene and its detection are the 2 significant testing errands in the moving video investigation system which is dynamic in nature. It is trying because of impediment, nearness of shadows, jumbling, dynamic foundation, clamor etc. Detection of moving objects, following, object coordinating crosswise over multi-camera, and reidentification are the fundamental strides of multi camera video investigation system. Multiple object location and following in savvy city video investigation can be created by propriety of society, for example, shrewd observation, savvy stopping, traffic observing, vehicle route, savvy human services and so forth. The objective of this paper is to examine and audit different methodologies towards such different types of moving object detection, its segmentation, histogram equalization, filtering, classification etc… Also, this survey paper gives a brief idea about the work done by various authors till date in the field of video image processing so that this review papers serves as a base paper for many of the researchers who want to do research in this exciting field of video processing. Some of the drawbacks or the disadvantages of the works that were carried out by the earlier researchers are considered in our research work, studied in brief & problem is being defined along with the objectives in order to overcome some of the deficiencies of the existing algos.

Efficient and robust Pedestrian Detection using Deep Learning for Human-Aware Navigation

This paper addresses the problem of Human-Aware Navigation (HAN), using multi camera sensors to implement a vision-based person tracking system. The main contributions of this paper are as follows: a novel and efficient Deep Learning person detection and a standardization of human-aware constraints. In the first stage of the approach, we propose to cascade the Aggregate Channel Features (ACF) detector with a deep Convolutional Neural Network (CNN) to achieve fast and accurate Pedestrian Detection (PD). Regarding the human awareness (that can be defined as constraints associated with the robot’s motion), we use a mixture of asymmetric Gaussian functions, to define the cost functions associated to each constraint. Both methods proposed herein are evaluated individually to measure the impact of each of the components. The final solution (including both the proposed pedestrian detection and the human-aware constraints) is tested in a typical domestic indoor scenario, in four distinct experiments. The results show that the robot is able to cope with human-aware constraints, defined after common proxemics and social rules.

Camera network analysis for visual surveillance in electric industrial context

Society is rapidly accepting the use of a wide variety of cameras location and applications: site traffic monitoring, parking lot surveillance, car and smart space. The camera provides data every day in an analysis by an effective way. Recent advances in sensor technology manufacturing, communications and computing are stimulating. The development of new applications that can change the traditional vision system incorporating universal smart camera network was processed. This analysis of visual cues in multi camera networks makes wide applications ranging from smart home and office automation to large area surveillance and traffic surveillance. And dense Camera networks, most of which have large overlapping areas of cameras. In the view of good research, we focus on sparse camera networks. One sparse camera network using large area surveillance was developed. As few cameras as possible, most cameras do not overlap each other’s field of vision. This task is challenging. Lack of knowledge of topology network, the specific changes in appearance and movement track different opinions of the target, as well as difficulties understanding complex events in a network were observed. In this review, we present a comprehensive survey of recent studies. Results to solve the problem of topology learning, object appearance modeling and global activity understanding sparse camera network were determined. In addition, some of the current open research issues are discussed.

Comparison of forensic photo-documentation to a photogrammetric solution using the multi-camera system “Botscan”

As forensic science technologies progress, digital photography has become outdated for certain documentations that require exact measurements. Recording three-dimensional objects on a two-dimensional photograph leads to a potential loss of relevant information. Photogrammetry has been utilized to record persons, objects or crime scenes and prevents this loss. Photogrammetry enables accurate documentation and visualization of events or matching of injuries and injury-causing instruments. To reduce inaccuracies during photogrammetric recording, a multi camera device, Botscan by Botspot, can be used to record living persons in three-dimensional space (3D). The device can record a full body in a fraction of a second, which leads to a significant reduction of inaccuracies due to movement. Photogrammetric measurements were compared with measurements from forensic photographs to evaluate the applicability of this device for medical forensic documentation of injuries. For this purpose, a mannequin fitted with different types of artificial injuries was used as an example. The results showed that the photogrammetric measurements obtained using the software Agisoft PhotoScan were more accurate than the measurements from the forensic photographs.

Design of an Embedded Multi-Camera Vision System—A Case Study in Mobile Robotics

The purpose of this work is to explore the design principles for a Real-Time Robotic Multi Camera Vision System, in a case study involving a real world competition of autonomous driving. Design practices from vision and real-time research areas are applied into a Real-Time Robotic Vision application, thus exemplifying good algorithm design practices, the advantages of employing the “zero copy one pass” methodology and associated trade-offs leading to the selection of a controller platform. The vision tasks under study are: (i) recognition of a “flat” signal; and (ii) track following, requiring 3D reconstruction. This research firstly improves the used algorithms for the mentioned tasks and finally selects the controller hardware. Optimization for the shown algorithms yielded from 1.5 times to 190 times improvements, always with acceptable quality for the target application, with algorithm optimization being more important on lower computing power platforms. Results also include a 3-cm and five-degree accuracy for lane tracking and 100% accuracy for signalling panel recognition, which are better than most results found in the literature for this application. Clear results comparing different PC platforms for the mentioned Robotic Vision tasks are also shown, demonstrating trade-offs between accuracy and computing power, leading to the proper choice of control platform. The presented design principles are portable to other applications, where Real-Time constraints exist.

Efficient large-scale graph data optimization for intelligent video surveillance

Society is rapidly accepting the use of a wide variety of cameras Location and applications: site traffic monitoring, parking Lot surveillance, car and smart space. These ones here the camera provides data every day in an analysis Effective way. Recent advances in sensor technology Manufacturing, communications and computing are stimulating.The development of new applications that can change the traditional Vision system incorporating universal smart camera network. This Analysis of visual cues in multi camera networks makes wide Applications ranging from smart home and office automation to large area surveillance and traffic surveillance. In addition, dense Camera networks, most of which have large overlapping areas of cameras. In the view of good research, we focus on sparse camera networks. One Sparse camera network using large area surveillance. As few cameras as possible, most cameras do not overlap Each other’s field of vision. This task is challenging Lack of knowledge of topology Network, the specific changes in appearance and movement Track different opinions of the target, as well as difficulties Understanding complex events in a network. In this review in this paper, we present a comprehensive survey of recent studies Results to solve the problem of topology learning, Object appearance modeling and global activity understanding sparse camera network. In addition, some of the current open Research issues are discussed.

The Direct Quantitative Measurement of In-Situ Burn (ISB) Rate and Efficiency

ABSTRACT In-situ burning (ISB) is an important tool to remove oil from the environment. During ISB, it is important to know the volume reduction of oil for the overall accounting of the spilled oil, as a metric for operational decisions, and to account for the ISB portion of the oil budget. The burn rate depends on the type of oil, degree of emulsification and weathering, estimated thickness, weather conditions, and size of the burn area. Furthermore, each spill has a unique physical environment and oil properties that affect burn efficiency and rate. The volume of oil consumed during ISB is typically computed using a manual, coarse, time integration of the instantaneous burn area based on visual observations and a characteristic burn rate. The area is typically estimated in the field using known boom geometry and visual inspection of the fire-water interface, and recorded manually. We have developed methods to measure the instantaneous consumption of burning oil and thus the oil burn rate by integrating direct measurements of thickness using acoustics sensors in the water under the slick with direct measurements of the area of the burning oil using infrared and visible light images from cameras above the burning oil. Data were collected during the burning of several oils and petroleum products including ANS, rock, diesel, and hexane. The acoustic thickness measurement took into account the high temperature gradient in the oil and combined with multi camera automated burn area estimates yielded an instantaneous measurement of the volume of oil consumed while burning. We were able to identify the buildup of the burn, the active burning phase, and in the case of confined burns the vigorous burning phase. Knowing the instantaneous thickness and surface area during burning allowed us to directly calculate the burn rate and to study the dynamics of ISB. We are working on validating the burn rate and efficiency with direct measurements of the weight of the oil and residue before, during, and after burning. The authors believe these are the first direct measurements of slick thickness using acoustics during ISB.

Image Based 3D Reconstruction of Texture-less Objects for VR Contents

Recent development in virtual and augmented reality increases the demand for content in many different fields. One of the fast ways to create content for VR is 3D modeling of real objects. In this paper we propose a system to reconstruct three-dimensional models of real objects from the set of two-dimensional images under the assumption that the subject does not has distinct features. We explicitly consider an object that is made of one or more surfaces and radiant constant energy isotropically. We design a low cost portable multi camera rig system that is capable of capturing images simultaneously from all cameras. In order to evaluate the performance of the proposed system, comparison is made between 3D model and a CAD model. A simple algorithm is also proposed to acquire original texture or color of the subject. Using best pattern found after the experiments, 3D model of the Pyeongchang Olympic Mascot “Soohorang” is created to use as VR content

Adaptive Vision Based Condition Monitoring and Fault Detection Method for Multi Robots at Production Lines in Industrial Systems

Continuity of production is a highly important in the days that manufacturing is becoming bigger and serial. The mistakes done while producing process cause fail on products and it may bring about even big losses for the facility. Furthermore, hitches on robots at production line may also cause crucial damages that may give rise to high repair costs and discontinuance of production. In this study, it is aimed to obtain alive bird's eye view map of production lines, which are big and impossible to be monitored with only one camera, by using multi cameras and stitching algorithms. Finding the similar scenes of input images, estimation of homography, warping and blending operations, which are the steps used in feature based image-stitching algorithms, are applied respectively on images that are taken by cameras. The assignment of second nearest neighbor distance rate adaptively makes the results more qualified. After obtaining single stitched image movement detection is actualized by using the difference of sequential frames, and anomaly movements are determined. As a result, the robots at the long production lines can be monitored in one screen, and with processing the obtained image, faults on robots that may cause damage at non-cheap machines can be handled before time.

Particle Filter -based Multitarget Multi camera Tracking System utilizing Random Finite Sets and Distributed Estimation Process

Particle Filter -based Multitarget Multi camera Tracking System utilizing Random Finite Sets and Distributed Estimation Process

Realization of Multi-User Tangible Non-Glasses Mixed Reality Space

Background/Objectives: Studies on convergent space, where multiple users can participate simultaneously, are lacking despite the spatial characteristic of mixed reality space where several people can coexist. Methods/Statistical Analysis: Based on the Unity3D engine, four-sided mapping was done using a multi camera in a CAVE type space. An autostereoscopic 3D image was provided by forming a parallax barrier using binocular disparity, and a space capable of multiple user participation was formed by implementing a multi-tracking system using Kinect. Findings: The development of technologies that allow autostereoscopic virtual reality and mixed reality experiences are currently underway, but a technology that can implement a mixed reality space for multiple users to experience virtual reality without special glasses in a real spatial environment is still in the development stage. The present study created an autostereoscopic 3D environment for resolving user discomfort, and implemented a multi-tracking system aimed at multiple user participation. As a result, the study was limited in that the definition of the screen differs depending on the light in accordance with the characteristics of beam projectors and that the restrictions to CAVE space only allows a restricted number of personnel to participate. Application/Improvements: Active research must be conducted on contents that are usable in mixed reality space implemented for vitalizing virtual reality space research.

ORIENTATION OF OBLIQUE AIRBORNE IMAGE SETS – EXPERIENCES FROM THE ISPRS/EUROSDR BENCHMARK ON MULTI-PLATFORM PHOTOGRAMMETRY

Abstract. During the last decade the use of airborne multi camera systems increased significantly. The development in digital camera technology allows mounting several mid- or small-format cameras efficiently onto one platform and thus enables image capture under different angles. Those oblique images turn out to be interesting for a number of applications since lateral parts of elevated objects, like buildings or trees, are visible. However, occlusion or illumination differences might challenge image processing. From an image orientation point of view those multi-camera systems bring the advantage of a better ray intersection geometry compared to nadir-only image blocks. On the other hand, varying scale, occlusion and atmospheric influences which are difficult to model impose problems to the image matching and bundle adjustment tasks. In order to understand current limitations of image orientation approaches and the influence of different parameters such as image overlap or GCP distribution, a commonly available dataset was released. The originally captured data comprises of a state-of-the-art image block with very high overlap, but in the first stage of the so-called ISPRS/EUROSDR benchmark on multi-platform photogrammetry only a reduced set of images was released. In this paper some first results obtained with this dataset are presented. They refer to different aspects like tie point matching across the viewing directions, influence of the oblique images onto the bundle adjustment, the role of image overlap and GCP distribution. As far as the tie point matching is concerned we observed that matching of overlapping images pointing to the same cardinal direction, or between nadir and oblique views in general is quite successful. Due to the quite different perspective between images of different viewing directions the standard tie point matching, for instance based on interest points does not work well. How to address occlusion and ambiguities due to different views onto objects is clearly a non-solved research problem so far. In our experiments we also confirm that the obtainable height accuracy is better when all images are used in bundle block adjustment. This was also shown in other research before and is confirmed here. Not surprisingly, the large overlap of 80/80% provides much better object space accuracy – random errors seem to be about 2-3fold smaller compared to the 60/60% overlap. A comparison of different software approaches shows that newly emerged commercial packages, initially intended to work with small frame image blocks, do perform very well.

ORIENTATION OF OBLIQUE AIRBORNE IMAGE SETS – EXPERIENCES FROM THE ISPRS/EUROSDR BENCHMARK ON MULTI-PLATFORM PHOTOGRAMMETRY

During the last decade the use of airborne multi camera systems increased significantly. The development in digital camera technology allows mounting several mid- or small-format cameras efficiently onto one platform and thus enables image capture under different angles. Those oblique images turn out to be interesting for a number of applications since lateral parts of elevated objects, like buildings or trees, are visible. However, occlusion or illumination differences might challenge image processing. From an image orientation point of view those multi-camera systems bring the advantage of a better ray intersection geometry compared to nadir-only image blocks. On the other hand, varying scale, occlusion and atmospheric influences which are difficult to model impose problems to the image matching and bundle adjustment tasks. In order to understand current limitations of image orientation approaches and the influence of different parameters such as image overlap or GCP distribution, a commonly available dataset was released. The originally captured data comprises of a state-of-the-art image block with very high overlap, but in the first stage of the so-called ISPRS/EUROSDR benchmark on multi-platform photogrammetry only a reduced set of images was released. In this paper some first results obtained with this dataset are presented. They refer to different aspects like tie point matching across the viewing directions, influence of the oblique images onto the bundle adjustment, the role of image overlap and GCP distribution. As far as the tie point matching is concerned we observed that matching of overlapping images pointing to the same cardinal direction, or between nadir and oblique views in general is quite successful. Due to the quite different perspective between images of different viewing directions the standard tie point matching, for instance based on interest points does not work well. How to address occlusion and ambiguities due to different views onto objects is clearly a non-solved research problem so far. In our experiments we also confirm that the obtainable height accuracy is better when all images are used in bundle block adjustment. This was also shown in other research before and is confirmed here. Not surprisingly, the large overlap of 80/80% provides much better object space accuracy – random errors seem to be about 2-3fold smaller compared to the 60/60% overlap. A comparison of different software approaches shows that newly emerged commercial packages, initially intended to work with small frame image blocks, do perform very well.

3D Perception Technologies for Surgical Operating Theatres.

3D Perception technologies have been explored in various fields. This paper explores the application of such technologies for surgical operating theatres. Clinical applications can be found in workflow detection, tracking and analysis, collision avoidance with medical robots, perception of interaction between participants of the operation, training of the operation room crew, patient calibration and many more. In this paper a complete perception solution for the operating room is shown. The system is based on the ToF technology integrated to the Microsoft Kinect One implements a multi camera approach. Special emphasize is put on the tracking of the personnel and the evaluation of the system performance and accuracy.

A new approach for real time object detection and tracking on high resolution and multi-camera surveillance videos using GPU

High resolution cameras and multi camera systems are being used in areas of video surveillance like security of public places, traffic monitoring, and military and satellite imaging. This leads to a demand for computational algorithms for real time processing of high resolution videos. Motion detection and background separation play a vital role in capturing the object of interest in surveillance videos, but as we move towards high resolution cameras, the time-complexity of the algorithm increases and thus fails to be a part of real time systems. Parallel architecture provides a surpass platform to work efficiently with complex algorithmic solutions. In this work, a method was proposed for identifying the moving objects perfectly in the videos using adaptive background making, motion detection and object estimation. The pre-processing part includes an adaptive block background making model and a dynamically adaptive thresholding technique to estimate the moving objects. The post processing includes a competent parallel connected component labelling algorithm to estimate perfectly the objects of interest. New parallel processing strategies are developed on each stage of the algorithm to reduce the time-complexity of the system. This algorithm has achieved a average speedup of 12.26 times for lower resolution video frames (320×240, 720×480, 1024×768) and 7.30 times for higher resolution video frames (1360×768, 1920×1080, 2560×1440) on GPU, which is superior to CPU processing. Also, this algorithm was tested by changing the number of threads in a thread block and the minimum execution time has been achieved for 16×16 thread block. And this algorithm was tested on a night sequence where the amount of light in the scene is very less and still the algorithm has given a significant speedup and accuracy in determining the object.

Multi camera triggering and synchronization issue : case study

Multi camera triggering and synchronization issue : case study

Design and Implementation of an Automatic Face-image Data Acquisition System using IP Based Multi Camera

Design and Implementation of an Automatic Face-image Data Acquisition System using IP Based Multi Camera