Showing papers on "Smart camera published in 2010"

Self-contained wireless camera device, wireless camera system and method

Abstract: A self-contained wireless camera ( 10 ) and a wireless camera system ( 25 ) having such a device and a base station ( 20 ). Video processing (e.g. video compression) circuitry ( 200, 210 ) of the camera device receives video signals from a camera ( 130 ) and provides processed video signals. These are transmitted over a shared radio channel. A radio receiver ( 101 ) receives processed (e.g. compressed) video signals from the base station or another camera device. Images from the camera or the base station are displayed in a selected manner on a display or monitor ( 140 ). The base station device ( 20 ) receives processed (e.g. compressed) video signals, stores them and retransmits them. A command signal is received by the radio receiver to modify operation in such a manner as to control bandwidth usage. Wireless camera devices can adjust their operation to accommodate other wireless camera devices. Different transport protocol modules 230 and 240 can be selected according to the application that the user selects for operation.

The recognition and tracking of traffic lights based on color segmentation and CAMSHIFT for intelligent vehicles

Abstract: The recognition and tracking of traffic lights for intelligent vehicles based on a vehicle-mounted camera are studied in this paper. The candidate region of the traffic light is extracted using the threshold segmentation method and the morphological operation. Then, the recognition algorithm of the traffic light based on machine learning is employed. To avoid false negatives and tracking loss, the target tracking algorithm CAMSHIFT (Continuously Adaptive Mean Shift), which uses the color histogram as the target model, is adopted. In addition to traffic signal pre-processing and the recognition method of learning, the initialization problem of the search window of CAMSHIFT algorithm is resolved. Moreover, the window setting method is used to shorten the processing time of the global HSV color space conversion. The real vehicle experiments validate the performance of the presented approach.

Methods and systems for determining the pose of a camera with respect to at least one object of a real environment

Abstract: Method for determining the pose of a camera with respect to at least one object of a real environment for use in authoring/augmented reality application that includes generating a first image by the camera capturing a real object of a real environment, generating first orientation data from at least one orientation sensor associated with the camera or from an algorithm which analyses the first image for finding and determining features which are indicative of an orientation of the camera, allocating a distance of the camera to the real object, generating distance data indicative of the allocated distance, determining the pose of the camera with respect to a coordinate system related to the real object of the real environment using the distance data and the first orientation data. May be performed with reduced processing requirements and/or higher processing speed, in mobile device such as mobile phones having display, camera and orientation sensor.

System and method for providing depth adaptive video conferencing

Abstract: A method is provided in one example and includes capturing panoramic image data through a first camera in a camera cluster, and capturing close-up image data through a second camera included as part of a spaced array of cameras. The presence of a user in a field of view of the second camera can be detected. The close-up image data and the panoramic image data can be combined to form a combined image. In more specific embodiments, the detecting includes evaluating a distance between the user and the second camera. The combined image can reflect a removal of a portion of panoramic image data associated with the user in a video conferencing environment.

Tasking networked CCTV cameras and mobile phones to identify and localize multiple people

Abstract: We present a method to identify and localize people by leveraging existing CCTV camera infrastructure along with inertial sensors (accelerometer and magnetometer) within each person's mobile phones. Since a person's motion path, as observed by the camera, must match the local motion measurements from their phone, we are able to uniquely identify people with the phones' IDs by detecting the statistical dependence between the phone and camera measurements. For this, we express the problem as consisting of a two-measurement HMM for each person, with one camera measurement and one phone measurement. Then we use a maximum a posteriori formulation to find the most likely ID assignments. Through sensor fusion, our method largely bypasses the motion correspondence problem from computer vision and is able to track people across large spatial or temporal gaps in sensing. We evaluate the system through simulations and experiments in a real camera network testbed.

Video Analysis in Pan-Tilt-Zoom Camera Networks

Abstract: Pan-tilt-zoom (PTZ) cameras are able to dynamically modify their field of view (FOV). This functionality introduces new capabilities to camera networks such as increasing the resolution of moving targets and adapting the sensor coverage. On the other hand, PTZ functionality requires solutions to new challenges such as controlling the PTZ parameters, estimating the ego motion of the cameras, and calibrating the moving cameras.This tutorial provides an overview of the main video processing techniques and the currents trends in this active field of research. Autonomous PTZ cameras mainly aim to detect and track targets with the largest possible resolution. Autonomous PTZ operation is activated once the network detects and identifies an object as sensible target and requires accurate control of the PTZ parameters and coordination among the cameras in the network. Therefore, we present cooperative localization and tracking methods, i.e., multiagentand consensus-based approaches to jointly compute the target's properties such as ground-plane position and velocity. Stereo vision exploiting wide baselines can be used to derive three-dimensional (3-D) target localization. This tutorial further presents different techniques for controlling PTZ camera handoff, configuring the network to dynamically track targets, and optimizing the network configuration to increase coverage probability. It also discusses implementation aspects for these video processing techniques on embedded smart cameras, with a special focus on data access properties.

Distributed target tracking using self localizing smart camera networks

Abstract: This paper describes a novel decentralized target tracking scheme for distributed smart cameras. This approach is built on top of a distributed localization protocol which allows the smart camera nodes to automatically identify neighboring sensors with overlapping fields of regard and establish a communication graph which reflects how the nodes will interact to fuse measurements in the network. The new protocol distributes the detection and tracking problems evenly throughout the network accounting for sensor handoffs in a seamless manner. The approach also distributes knowledge about the state of tracked objects amongst the nodes in the network. This information can then be harvested through distributed queries which allow network participants to subscribe to different kinds of events that they may be interested in. The proposed scheme has been used to track targets in real time using a collection of custom designed smart camera nodes. Results from these experiments are presented.

Image processing for a dual camera mobile device

Abstract: Some embodiments provide a method of processing images for a first camera and a second camera of a mobile device using a shared pipeline. A method receives a first set of images captured by the first camera of the mobile device. The method processes the first set of images using a first configuration of the shared pipeline. The method also receives a second set of images captured by the second camera of the mobile device, and processes the second set of images using a second configuration of the shared pipeline different from the first configuration.

Review on camera calibration

Abstract: The camera calibration has become one of the most important parts of computer vision By doing this, we can obtain the intrinsic and extrinsic parameters of cameras This paper introduces the widespread application of camera calibration in the robot navigation, the three-dimensional reconstruction, the bio-medical, the virtual reality and the visual surveillance Then summarizes the methods in different application, such as traditional calibration, the self-calibration and the active vision calibration

TrustCAM: Security and Privacy-Protection for an Embedded Smart Camera Based on Trusted Computing

Abstract: Security and privacy protection are critical issues forpublic acceptance of camera networks Smart cameras,with onboard image processing, can be used to identifyand remove privacy sensitive image regions Existing approaches,however, only address isolated aspects withoutconsidering the integration with established security technologiesand the underlying platform This work tries to fillthis gap and presents TrustCAM, a security-enhanced smartcamera Based on Trusted Computing, we realize integrityprotection, authenticity and confidentiality of image dataMultiple levels of privacy protection, together with accesscontrol, are supported Impact on overall system performanceis evaluated on a real prototype implementation

Cooperative Object Tracking and Composite Event Detection With Wireless Embedded Smart Cameras

Abstract: Embedded smart cameras have limited processing power, memory, energy, and bandwidth. Thus, many system- and algorithm-wise challenges remain to be addressed to have operational, battery-powered wireless smart-camera networks. We present a wireless embedded smart-camera system for cooperative object tracking and detection of composite events spanning multiple camera views. Each camera is a CITRIC mote consisting of a camera board and wireless mote. Lightweight and robust foreground detection and tracking algorithms are implemented on the camera boards. Cameras exchange small-sized data wirelessly in a peer-to-peer manner. Instead of transferring or saving every frame or trajectory, events of interest are detected. Simpler events are combined in a time sequence to define semantically higher-level events. Event complexity can be increased by increasing the number of primitives and/or number of camera views they span. Examples of consistently tracking objects across different cameras, updating location of occluded/lost objects from other cameras, and detecting composite events spanning two or three camera views, are presented. All the processing is performed on camera boards. Operating current plots of smart cameras, obtained when performing different tasks, are also presented. Power consumption is analyzed based upon these measurements.

Power control method of gesture recognition device by detecting presence of user

Abstract: Provided is a method which reduces the power consumption of a camera for detecting a user's gesture, in a device that detects the user's gesture and performs a command corresponding to the detected gesture Moreover, provided is a method which turns off a camera or drives the camera in an ultra low power mode when there is no user input, and detects presence of a user to activate the camera

A Bus-Based SoC Architecture for Flexible Module Placement on Reconfigurable FPGAs

Abstract: This paper proposes an FPGA-based System-on-Chip (SoC) architecture with support for dynamic runtime reconfiguration. The SoC is divided into two parts, the static embedded CPU sub-system and the dynamically reconfigurable part. An additional bus system connects the embedded CPU sub-system with modules within the dynamic area, offering a flexible way to communicate among all SoC components. This makes it possible to implement a reconfigurable design with support for free module placement. An enhanced memory access method is included for high-speed access to an external memory. The dynamic part includes a streaming technology which implements a direct connection between reconfigurable modules. The paper describes the architecture and shows the advantages in a smart camera case study.

Video capture system control using virtual cameras for augmented reality

Abstract: There is provided a system and method for integrating a virtual rendering system and a video capture system using flexible camera control to provide an augmented reality There is provided a method for integrating a virtual rendering system and a video capture system for outputting a composite render to a display, the method comprising obtaining, from the virtual rendering system, a virtual camera configuration of a virtual camera in a virtual environment, programming the video capture system using the virtual camera configuration to correspondingly control a robotic camera in a real environment, capturing a video capture feed using the robotic camera, obtaining a virtually rendered feed using the virtual camera, rendering the composite render by processing the feeds, and outputting the composite render to the display

Towards an efficient distributed object recognition system in wireless smart camera networks

Abstract: We propose an efficient distributed object recognition system for sensing, compression, and recognition of 3-D objects and landmarks using a network of wireless smart cameras. The foundation is based on a recent work that shows the representation of scale-invariant image features exhibit certain degree of sparsity: If a common object is observed by multiple cameras from different vantage points, the corresponding features can be efficiently compressed in a distributed fashion, and the joint signals can be simultaneously decoded based on distributed compressive sensing theory. In this paper, we first present a public multiple-view object recognition database, called the Berkeley Multiview Wireless (BMW) database. It captures the 3-D appearance of 20 landmark buildings sampled by five low-power, low-resolution camera sensors from multiple vantage points. Then we review and benchmark state-of-the-art methods to extract image features and compress their sparse representations. Finally, we propose a fast multiple-view recognition method to jointly classify the object observed by the cameras. To this end, a distributed object recognition system is implemented on the Berkeley CITRIC smart camera platform. The system is capable of adapting to different network configurations and the wireless bandwidth. The multiple-view classification improves the performance of object recognition upon the traditional per-view classification algorithms.

Collaborative occupancy reasoning in visual sensor network for scalable smart video surveillance

Abstract: Video surveillance is a popular consumer application that is used for various purposes such as public safety, facilities surveillance, and traffic monitoring In a general video surveillance system, video streams from cameras are sent to a control center and operators monitor the videos But human operator monitoring of the views every moment of every day is almost impossible; so, smart surveillance systems are required, systems that are capable of automated scene analysis There are a number of studies to enable smart video surveillance in a multi-camera network Most of the studies, however, treat central processing approaches in which a scene analysis is processed inside a central server domain once all available information has been collected in the server Such approaches require tremendous efforts in building the system and, moreover, limit the scalability To accomplish scalable smart video surveillance, an inference framework in visual sensor networks is necessary, one in which autonomous scene analysis is performed via distributed and collaborative processing among camera nodes without necessity for a high performance server In this paper, we propose a collaborative inference framework for visual sensor networks and an efficient occupancy reasoning algorithm that is essential in smart video surveillance based on the framework We estimate the existence probabilities for every camera and combine them using the work-tree architecture in a distributed and collaborative manner We aim for practical smart video surveillance systems

An energy efficient multimodal Wireless Video Sensor Network with eZ430–RF2500 modules

Abstract: In video surveillance there is an ever-growing demand for heavily distributed radio cooperating objects that Wireless Sensor Networks (WSNs) can satisfy. We present a preliminary study of an energy efficient multimodal WVSN using a main node deciding which camera to trigger based on the information from a Pyroelectric InfraRed (PIR) network. The evaluation of the proposed approach against the solution with PIRs onboard shows significantly reduced cameras' ON-time, enabling network lifetime prolongation up to 75%. Furthermore, including cameras ' available energy in wake-up rules, which would be significant for the networks comprising a photovoltaic power source, augments additionally the system's lifetime. The performance of our approach is evaluated in MATLAB simulation.

A Distributed Topological Camera Network Representation for Tracking Applications

Abstract: Sensor networks have been widely used for surveillance, monitoring, and tracking. Camera networks, in particular, provide a large amount of information that has traditionally been processed in a centralized manner employing a priori knowledge of camera location and of the physical layout of the environment. Unfortunately, these conventional requirements are far too demanding for ad-hoc distributed networks. In this article, we present a simplicial representation of a camera network called the camera network complex (CN-complex), that accurately captures topological information about the visual coverage of the network. This representation provides a coordinate-free calibration of the sensor network and demands no localization of the cameras or objects in the environment. A distributed, robust algorithm, validated via two experimental setups, is presented for the construction of the representation using only binary detection information. We demonstrate the utility of this representation in capturing holes in the coverage, performing tracking of agents, and identifying homotopic paths.

Versatile dual mode wireless camera hotspot device

Abstract: A versatile dual mode wireless camera hotspot and method. The method comprises capturing data comprising at least one of video and audio from a camera. The camera has a transmitter and receiver integrated with the camera. The camera further provides a wireless access point to allow access to a network.

Video surveillance system and associated methods

Abstract: A video surveillance system includes a video camera and a video data management device in communication with the video camera. The video data management device has a server providing a programmable interface for camera control and video management, a router in communication with the server to provide broadband internet access to the server, and a data storage device.

Action Selection for Single-Camera SLAM

Abstract: A method for evaluating, at video rate, the quality of actions for a single camera while mapping unknown indoor environments is presented. The strategy maximizes mutual information between measurements and states to help the camera avoid making ill-conditioned measurements that are appropriate to lack of depth in monocular vision systems. Our system prompts a user with the appropriate motion commands during 6-DOF visual simultaneous localization and mapping with a handheld camera. Additionally, the system has been ported to a mobile robotic platform, thus closing the control-estimation loop. To show the viability of the approach, simulations and experiments are presented for the unconstrained motion of a handheld camera and for the motion of a mobile robot with nonholonomic constraints. When combined with a path planner, the technique safely drives to a marked goal while, at the same time, producing an optimal estimated map.

GIS-augmented video surveillance

Abstract: Registration in augmented reality is a process that merges virtual objects generated by a computer with real-world images captured by a camera. In this article, we present a method for registration of geospatial data applicable to outdoor video surveillance systems consisting of several PTZ cameras. PTZ is an abbreviation for pan-tilt-zoom, and in the terminology of video surveillance it indicates cameras that can rotate in the horizontal (pan) and vertical planes (tilt) and change their level of magnification (zoom). Registration is based on transforming these relative camera view parameters into the absolute position, orientation and field of view required by the three-dimensional geographic information systems (3D GISs). Once the 3D GIS and camera views are aligned, it is possible to identify geospatial objects from the camera image, as well as to overlap the virtual scene with the real one. In addition, inverse transformation of the view parameters allows for selecting and pointing the appropriate camera to some geo-referenced feature or event. Based on the proposal, we developed GeoScopeAVS, a GIS-based system for augmented video surveillance and suggested application of such a system in emergency situation management and urban planning.

Scalable target coverage in smart camera networks

Abstract: Smart camera networks are becoming increasingly popular in a number of application domains. In many applications, cameras are required to collaboratively track objects (e.g., habitat monitoring, or surveillance). In smart networks, camera coverage control is necessary to allow automatic tracking of targets without human intervention, allowing these systems to scale. In this paper, we consider the problem of automatic control of the cameras to maximize coverage of a set of targets. We formulate an optimization problem with the goal of maximizing the number of covered targets. Since the optimization problem is NP-hard, even for static targets, we propose a computationally efficient heuristic to reach near-optimal solution. Centralized solutions achieve excellent coverage, and can work well for small-scale networks, however they require significant communication cost for large scale networks. As a result, we propose an algorithm that spatially decomposes the network and computes optimal solutions for individual partitions. By decomposing the partitions in a way that minimizes dependencies between them, this approach results in coverage quality close to the centralized optimal solution, with an overhead and reaction time similar to those of distributed solutions.

Interactive media system with multi-directional remote control and dual mode camera

Abstract: A multi-directional remote control system and method is adapted for use with an interactive media system of a type including a display such as a monitor or TV with a camera. The remote control system and method images the controller to detect relative motion between the controller and screen with the camera. This position information is used for control of a cursor or other GUI interface. A movable IR filter improves detection of the IR during tracking and allows the camera to have a second function, such as a web cam or other function, with the filter not in place.

Systems and methods for acquiring and processing image data produced by camera arrays

Abstract: This disclosure is directed to camera systems including a camera array, data buses shared by the cameras, and one or more processors that process images captured by the camera array. In one aspect, a camera system (450) includes a camera array (452), a controller (454), a number of camera buses (458-465), and a computing device (456) connected to the controller. Each camera is connected to one or more adjacent cameras and includes one or more processors. Each camera bus connects a subset of cameras of the camera array to the controller. And each camera can be operated to send to the controller only the image data used by the computing device to generate virtual images and receive instructions from the controller over a camera bus.

A systematic approach towards user-centric privacy and security for smart camera networks

Abstract: The majority of research in the field of camera networks is targeted at distributed and cooperative processing, advanced computer vision algorithms or the development of embedded, ubiquitous camera systems. Privacy and security are topics that are often overlooked or considered as an afterthought. With the digitalization of visual surveillance, data can easily be stored and accessed. This raises the question how confidential data can be protected, authenticity and integrity can be ensured and access can be restricted. This work discusses security and privacy issues relevant in the context of visual surveillance and camera networks. We try to capture the state of the art on these aspects in the available literature and highlight areas that require special consideration. We present a concept of a privacy-preserving camera system based on Trusted Computing. In our system-level approach, we consider privacy and security as primary goals without limiting the overall usefulness of a camera system.