Camera Selection Research Articles

ViComp: composition of user-generated videos

We propose ViComp, an automatic audio-visual camera selection framework for composing uninterrupted recordings from multiple user-generated videos (UGVs) of the same event. We design an automatic audio-based cut-point selection method to segment the UGV. ViComp combines segments of UGVs using a rank-based camera selection strategy by considering audio-visual quality and camera selection history. We analyze the audio to maintain audio continuity. To filter video segments which contain visual degradations, we perform spatial and spatio-temporal quality assessment. We validate the proposed framework with subjective tests and compare it with state-of-the-art methods.

Camera selection for real-time in vivo radiation treatment verification systems using Cherenkov imaging.

To identify achievable camera performance and hardware needs in a clinical Cherenkov imaging system for real-time, in vivo monitoring of the surface beam profile on patients, as novel visual information, documentation, and possible treatment verification for clinicians. Complementary metal-oxide-semiconductor (CMOS), charge-coupled device (CCD), intensified charge-coupled device (ICCD), and electron multiplying-intensified charge coupled device (EM-ICCD) cameras were investigated to determine Cherenkov imaging performance in a clinical radiotherapy setting, with one emphasis on the maximum supportable frame rate. Where possible, the image intensifier was synchronized using a pulse signal from the Linac in order to image with room lighting conditions comparable to patient treatment scenarios. A solid water phantom irradiated with a 6 MV photon beam was imaged by the cameras to evaluate the maximum frame rate for adequate Cherenkov detection. Adequate detection was defined as an average electron count in the background-subtracted Cherenkov image region of interest in excess of 0.5% (327 counts) of the 16-bit maximum electron count value. Additionally, an ICCD and an EM-ICCD were each used clinically to image two patients undergoing whole-breast radiotherapy to compare clinical advantages and limitations of each system. Intensifier-coupled cameras were required for imaging Cherenkov emission on the phantom surface with ambient room lighting; standalone CMOS and CCD cameras were not viable. The EM-ICCD was able to collect images from a single Linac pulse delivering less than 0.05 cGy of dose at 30 frames/s (fps) and pixel resolution of 512 × 512, compared to an ICCD which was limited to 4.7 fps at 1024 × 1024 resolution. An intensifier with higher quantum efficiency at the entrance photocathode in the red wavelengths [30% quantum efficiency (QE) vs previous 19%] promises at least 8.6 fps at a resolution of 1024 × 1024 and lower monetary cost than the EM-ICCD. The ICCD with an intensifier better optimized for red wavelengths was found to provide the best potential for real-time display (at least 8.6 fps) of radiation dose on the skin during treatment at a resolution of 1024 × 1024.

Design of Endoscopic Capsule With Multiple Cameras.

In order to reduce the miss rate of the wireless capsule endoscopy, in this paper, we propose a new system of the endoscopic capsule with multiple cameras. A master-slave architecture, including an efficient bus architecture and a four level clock management architecture, is applied for the Multiple Cameras Endoscopic Capsule (MCEC). For covering more area of the gastrointestinal tract wall with low power, multiple cameras with a smart image capture strategy, including movement sensitive control and camera selection, are used in the MCEC. To reduce the data transfer bandwidth and power consumption to prolong the MCEC's working life, a low complexity image compressor with PSNR 40.7 dB and compression rate 86% is implemented. A chipset is designed and implemented for the MCEC and a six cameras endoscopic capsule prototype is implemented by using the chipset. With the smart image capture strategy, the coverage rate of the MCEC prototype can achieve 98% and its power consumption is only about 7.1 mW.

Distributed Topological Camera Selection Without Location Information

In this paper, a distributed algorithm, namely distributed topological camera selection, is proposed for selecting the minimum number of cameras to cover the entire area in the case that there is no location information. In order to relax the location information assumption, we propose an approach based on homology. We consider the nerve complex corresponding to the camera network and demonstrate how combinatorial Laplacian and topological properties of the network can be used to formulate the problem of selecting the minimum number of cameras for covering the entire space as an optimization problem. Proposed optimization problem works on the simplicial complex of the network and finds the least number of two-simplices that cover the entire area. Then, we propose a distributed algorithm using the subgradient method for this problem. Finally, we validate the algorithm via one experimental setup and evaluate the performance of the proposed algorithm by conducting simulations.

Game-Theoretic Camera Selection Using Inference Tree Method for a Wireless Visual Sensor Network

In a wireless visual sensor network consisting of wireless, battery-powered, and field-of-view (FoV) overlapping and stationary visual sensors, trade-offs exist between extending network lifetime and enhancing its sensing accuracy. Moreover, aggregating individual inferences from each sensor is essential to generate a globally consistent inference, because these individual inferences can be biased by noise or other unexpected conditions. Those challenges can be addressed by reducing the amount of data transmission among the sensors and by activating, in a timely manner, only a desirable camera subset for given targets. In this paper, we initialize an optimal data transmission path among visual sensors using the inference tree method, which is vital for collecting individual inferences and building a global inference. Based on the optimal data transmission path, we model the camera selection problem in a cooperative bargaining game. In this game, based on the serial dictatorial rule, camera sensors cooperatively attempt to raise the overall sensing accuracy by sequentially deciding their own mode between “sleep” and “active” in descending order of their bargaining power. Simulated results demonstrate that our proposed approach outperforms other alternatives, resulting in reduced resource overhead and improved network lifetime and sensing accuracy.

Content/Context-aware Multiple Camera Selection and Video Adaptation for the Support of m-Health Services

In this paper we focus on the problem of delivering multiple health-related real-time video streams from an emer- gency scenario to a remote hospital by exploiting the uplink of an LTE wireless access network, in order to support efficient m-health tele-consultation services. In this context, the transmission of health-related information is a chal- lenging task, due to the variability and the limitations of the mobile radio link, the different qualities of the visual representations of the cameras and the heterogeneous end-to-end quality requirements of the contents to be delivered. We propose a solution based on: (i) a context-aware camera selection algorithm, which selects among the cameras deployed in the emergency scenario one or more video sources taking into account specific ranking criteria mainly related to the quality of the visual representation of the object of interest; (ii) a content-aware technique for the trans- mission of multiple scalable videos that jointly considers video aggregation and adaptation at the application layer of the transmitting equipment and takes into account the different quality requirements of diagnostic and ambient videos. Numerical results show that the proposed strategy permits to achieve a good end-to-end quality for both the diagnostic and the ambient videos even in the presence of rate limitations and fluctuations in the wireless link, due to the channel variations and the traffic load inside the LTE cell. When the wireless link capacity decreases, the proposed strategy appropriately discards the videos coming from the cameras providing the lowest visual quality, according to the camera ranking results, and, at the same time, adapts the rate of the transmitted videos to provide the requested quality with priority to diagnostic content.

Camera selection for tracking in distributed smart camera networks

Tracking persons with multiple cameras with overlapping fields of view instead of with one camera leads to more robust decisions. However, operating multiple cameras instead of one requires more processing power and communication bandwidth, which are limited resources in practical networks. When the fields of view of different cameras overlap, not all cameras are equally needed for localizing a tracking target. When only a selected set of cameras do processing and transmit data to track the target, a substantial saving of resources is achieved. The recent introduction of smart cameras with on-board image processing and communication hardware makes such a distributed implementation of tracking feasible. We present a novel framework for selecting cameras to track people in a distributed smart camera network that is based on generalized information-theory. By quantifying the contribution of one or more cameras to the tracking task, the limited network resources can be allocated appropriately, such that the best possible tracking performance is achieved. With the proposed method, we dynamically assign a subset of all available cameras to each target and track it in difficult circumstances of occlusions and limited fields of view with the same accuracy as when using all cameras.

High Performance Imaging through Occlusion via Energy Minimization-Based Optimal Camera Selection

Seeing an object in a cluttered scene with severe occlusion is a significantly challenging task for many computer vision applications. Although camera array synthetic aperture imaging has proven to be an effective way for occluded object imaging, its imaging quality is often significantly decreased by the shadows of the foreground occluder. To overcome this problem, some recent research has been presented to label the foreground occluder via object segmentation or 3D reconstruction. However, these methods usually fail in the case of complicated occluder or severe occlusion. In this paper, we present a novel optimal camera selection algorithm to handle the problem above. Firstly, in contrast to the traditional synthetic aperture photography methods, we formulate the occluded object imaging as a problem of visible light ray selection from the optimal camera view. To the best of our knowledge, this is the first time to “mosaic” a high quality occluded object image via selecting multi-view optimal visible light rays from a camera array or a single moving camera. Secondly, a greedy optimization framework is presented to propagate the visibility information among various depth focus planes. Thirdly, a multiple label energy minimization formulation is designed in each plane to select the optimal camera view. The energy is estimated in the 3D synthetic aperture image volume and integrates the multiple view intensity consistency, previous visibility property and camera view smoothness, which is minimized via graph cuts. Finally, we compare this approach with the traditional synthetic aperture imaging algorithms on UCSD light field datasets and our own datasets captured in indoor and outdoor environment, and extensive experimental results demonstrate the effectiveness and superiority of our approach.

How to take a good clinical photograph: camera selection and image quality

Aesthetic nurses will often take before and after photographs of their patients to document their clinical practice and show the patient the extent of the aesthetic effects that have been achieved following treatment. However, to make the most of this opportunity and remain cost-effective, it is beneficial for practitioners to have guidance on what makes a good photograph, and what tools are needed for this. In this article, the author outlines the important and valuable functions of today's vast range of cameras.

Collaborative routing and camera selection for visual wireless sensor networks

The authors propose a new approach for network lifetime maximisation in visual wireless sensor networks (VWSN). The existence of redundant multiple sensing for some parts of the field results in additional computational complexity and requires more bandwidth and battery power in the nodes, hence reducing the network lifetime. In a VWSN, efficient node collaboration for data sensing and gathering is a key factor to determine network lifetime. The proposed approach provides a jointly optimised traffic routing and camera selection strategy to enhance the lifetime of the whole network. In this approach, different nodes can collaborate with each other to prevent unnecessary multiple sensing of different areas in the network, and at the same time collaborate in the routing of the generated traffics to the network sink.

A fuzzy decision support system for digital camera selection based on user preferences

Mobile phones have been the most rapidly spreading development in the field of communication and information technologies over the past decades. Nowadays, digital cameras have taken their place. The wide product range in the market, each with numerous heterogeneous technical attributes, complicates the selection of the most convenient camera for end-users. The aim of this work is to provide end-users with a decision support framework for selecting the best digital camera according to their preferences. End-users and photography experts use subjective assessments when determining their requirements and making their evaluations. The proposed decision support tool is built on the basis of fuzzy set theory. The imprecision of the subjective assessments are transformed to fuzzy triangular numbers. The fuzzy analytic hierarchy process (FAHP) and fuzzy compromise programming methodologies are applied in order to determine the relative weights of sub-criteria and criteria and to rank the digital camera alternatives, respectively.

Design of a Parallel Face Detection Algorithm for Distributed Low Cost IP-based Surveillance Systems

In an environment with high secure requirement, multiple video surveillance devices may be installed in the secure environment. In this paper, a multi-camera surveillance system is built for these environments by a set of low-cost IP-based video surveillance cameras. An embedded distributed computing library, called D2MCE, is used to support the distributed computing. It provides a set of easy-to-use interfaces for the programmers to develop distributed parallel programs in a logically shared memory space. The proposed algorithm consists of four phases, including simultaneous intruder detection (SID), distributed camera selection (DCS), distributed & parallel face detection algorithm (DP-FDA), and automatic CAMShift face tracker (ACAM-FT). The advantage is that the system response time for the face detection will be shortened on the low-cost embedded IP-cameras without the help of expensive server machines. The system has been implemented on a set of the Intel PXA270 embedded platforms. Experiment results show that good performance can be achieved on the system.

A Dissonance Reduction Method for Intuitionistic Fuzzy Multi-Criteria Decision-Making Problems

Considering that cognitive dissonance is regarded as a momentous psychological factor in the decision making, this study proposes new techniques not only to tackle multi-criteria decision making problems but also to reduce the cognitive dissonance yielded by the decision maker under intuitionistic fuzzy environment. By applying the intuitionistic fuzzy weighted averaging (IFWA) operator and the score function, the proposed method derives the optimal weights of criteria and generates the priority of alternatives from the mathematical programming. In order to diminish the dissonance, the attractiveness of alternatives is magnified as large as possible in the programming problem based on the Euclidean distance. A numerical example is given to demonstrate the detailed calculating procedure; besides, an empirical case concerning a digital camera selection problem is employed to ascertain the feasibility of the developed method. According to the empirical results, the optimal alternative calculated by the mathematical programming satisfies decision makers and indeed reduces the dissonance. This study comes up with a successful manner to effectively reduce the dissonance when decision makers face a multi-criteria decision making problem.

Development of a digital close-range photogrammetric bridge deflection measurement system

This paper introduces a new close-range photogrammetric bridge deflection measurement system that has high accuracy and efficiency, and can be conveniently used by engineers without help from professional surveyors. After a general description of a photogrammetric bridge deflection measurement system, four critical components of the system are addressed in detail: camera selection and settings; camera calibration; network control (reference system and scale); and camera placement. The system configuration is introduced and the system is verified through the laboratory and field tests.

Multitarget Visual Tracking Based Effective Surveillance With Cooperation of Multiple Active Cameras

This paper presents a tracking-based surveillance system that is capable of tracking multiple moving objects, with almost real-time response, through the effective cooperation of multiple pan-tilt cameras. To construct this surveillance system, the distributed camera agent, which tracks multiple moving objects independently, is first developed. The particle filter is extended with target depth estimate to track multiple targets that may overlap with one another. A strategy to select the suboptimal camera action is then proposed for a camera mounted on a pan-tilt platform that has been assigned to track multiple targets within its limited field of view simultaneously. This strategy is based on the mutual information and the Monte Carlo method to maintain coverage of the tracked targets. Finally, for a surveillance system with a small number of active cameras to effectively monitor a wide space, this system is aimed to maximize the number of targets to be tracked. We further propose a hierarchical camera selection and task assignment strategy, known as the online position strategy, to integrate all of the distributed camera agents. The overall performance of the multicamera surveillance system has been verified with computer simulations and extensive experiments.

Real-time tracking of game assets in american football for automated camera selection and motion capture

In fast-paced games like American football, the action (and the viewers’ interest) often revolves around the location of key game assets, such as the football. It is difficult to track the football because it is often obscured or moving rapidly, essentially meaning that the broadcast-camera operators must manually track the football to provide feeds of the most interest. In this paper we describe the design and implementation of sensor-system that uses received signal strength data from multiple strategically placed sensor nodes to localize the game asset to an accurate camera region within a latency of 100ms. Using this real-time localization strategy, we can automate the control of broadcast cameras even in a fast-paced game with dramatically gamechanging moments (such as a kickoff return for a touchdown). This paper describes the design of the sensors, the network protocol, and the architecture of a deployable system in the field of play.

Pulsed eddy current thermography: system development and evaluation

There is a need for fast and efficient techniques to inspect engineering structures and complex components such as aircraft turbine blades to identify potential sites of failure. Pulsed eddy current (PEC) thermography is a new inspection technique which allows the user to capture the eddy current distribution in a component or structure using infrared imaging and detect defects over a relatively wide area. The technique is applicable to materials with a reasonable level of electrical conductivity and has the ability to detect defects under coatings. However, PEC thermography has received relatively little attention compared to other thermographic inspection techniques. In this paper, the design, development and optimisation of a PEC thermography inspection system is detailed, including coil design for global and local heating of samples, optimisation of excitation parameters (frequency, power, pulse duration etc) and camera selection. The system is used to inspect several real-world samples, using different coil designs, and the results are assessed using newly developed feature extraction techniques. The work shows that with judicious coil design and selection of excitation parameters, PEC thermography can be used to obtain quantitative information for defect characterisation through analysis of the surface heating pattern and the transient temperature change.

Personalized production of basketball videos from multi-sensored data under limited display resolution

Integration of information from multiple cameras is essential in television production or intelligent surveillance systems. We propose an autonomous system for personalized production of basketball videos from multi-sensored data under limited display resolution. The problem consists in selecting the right view to display among the multiple video streams captured by the investigated camera network. A view is defined by the camera index and the parameters of the image cropped within the selected camera. We propose criteria for optimal planning of viewpoint coverage and camera selection. Perceptual comfort is discussed as well as efficient integration of contextual information, which is implemented by smoothing generated viewpoint/camera sequences to alleviate flickering visual artifacts and discontinuous story-telling artifacts. We design and implement the estimation process and verify it by experiments, which shows that our method efficiently reduces those artifacts.

Adaptive online camera coordination for multi-camera multi-target surveillance

Online camera selection is introduced as a result of the improved mobility of cameras and the increased scale of surveillance systems. Most existing camera assignment algorithms achieve an optimal observation under the assumption of the unlimited camera computational capacities. However, practical surveillance systems experience resource limitation and see a degradation in the system performance as the number of objects to be processed increases. To address this issue, we propose an adaptive camera assignment algorithm considering the limited camera computational capacities. In so doing, camera resources can be dynamically allocated to multiple objects according to their priorities and the current camera computational load. Experimental results illustrate that the proposed camera assignment algorithm is capable of maintaining a constant frame rate and achieving a substantially decreased object rejection rate in comparison with the algorithm presented by Bakhtari and Benhabib.

A Cooperative Object Tracking System with Fuzzy-Based Adaptive Camera Selection

Abstract The intelligent environments, built upon many distributed sensors, are promising technology for ubiquitous interaction between robots and human beings. Especially, it is important to track target objects and get the positional information of them in such environments. This paper focuses on adapting camera selection for target tracking in multi-camera system. In this paper, a fuzzy automaton based camera selection method is introduced. In the proposed method, the camera selection decision is driven by fuzzy automaton based on the previously selected camera (previous camera state) and the tracking level of the object in each available camera. Simulations for evaluation of the proposed method and comparison with the previous method are presented. The results show that the proposed method is efficient for adaptive camera selection in multi-camera environment and helps easy construction of multi-camera placement. An actual multi-camera system with the proposed camera selection method was developed for checking tracking performance in the real environment. Experiments in the constructed system show that the proposed method suits well the camera selection task for tracking a moving object in the real intelligent environment.