Smart camera

About: Smart camera is a research topic. Over the lifetime, 5571 publications have been published within this topic receiving 93054 citations. The topic is also known as: intelligent camera.

External camera calibration for synchronized multi-video systems

Abstract: We present a method for external camera calibration that is simple to use and oers generality in the positioning of the cameras. This makes it very suitable for the calibration of mobile, synchronized camera setups. We use a camera graph to perform global registration which helps lifting restrictions on the camera setup imposed by other calibration methods. A further advantage is that all information is taken into account simultaneously. The method is based on a virtual calibration object which is constructed over time by tracking an easily identiable object through three-dimensional space. This implies that no calibration object must be visible simultaneously in all cameras.

A Convolutional Neural Network for Gender Recognition Optimizing the Accuracy/Speed Tradeoff

Abstract: Gender recognition has been among the most investigated problems in the last years; although several contributions have been proposed, gender recognition in unconstrained environments is still a challenging problem and a definitive solution has not been found yet. Furthermore, Deep Convolutional Neural Networks (DCNNs) achieve very interesting performance, but they typically require a huge amount of computational resources (CPU, GPU, RAM, storage), that are not always available in real systems, due to their cost or to specific application constraints (when the application needs to be installed directly on board of low-power smart cameras, e.g. for digital signage). In the latest years the Machine Learning community developed an interest towards optimizing the efficiency of Deep Learning solutions, in order to make them portable and widespread. In this work we propose a compact DCNN architecture for Gender Recognition from face images that achieves approximately state of the art accuracy at a highly reduced computational cost (almost five times). We also perform a sensitivity analysis in order to show how some changes in the architecture of the network can influence the tradeoff between accuracy and speed. In addition, we compare our optimized architecture with popular efficient CNNs on various common benchmark dataset, widely adopted in the scientific community, namely LFW, MIVIA-Gender, IMDB-WIKI and Adience, demonstrating the effectiveness of the proposed solution.

CAMEO: Camera Assisted Meeting Event Observer

Abstract: Static cameras are pervasive in a variety of environments. However it remains a challenging problem to extract and reason about high-level features from real-time and continuous observation of an environment. In this paper, we present CAMEO, the Camera Assisted Meeting Event Observer, which is a physical awareness system designed for use by an agent-based electronic assistant. CAMEO is an inexpensive high-resolution omnidirectional vision system designed to be used in meeting environments. The multiple camera design achieves the desired high image resolution and lower cost that can be achieved when compared to traditional omnicameras that make use of a single camera and mirror solution.

Mobile Standards-Based Traffic Light Detection in Assistive Devices for Individuals with Color-Vision Deficiency

Abstract: Considering the substantial population affected by some form of color-vision deficiency (CVD), reliable traffic control signal head light detection is an important problem for driver-assistance systems While a large number of technologies can be used to localize traffic lights, without drastic changes in infrastructure, only visual information can be used in identifying the status of the light In addition, traffic light detection is not currently integrated into any driver-assistance systems, making driving for individuals with CVD (where permitted) dangerous to other drivers, pedestrians, and themselves This paper presents a robust, traffic-standards-based, and computationally efficient method for detecting the status of the traffic lights without relying on Global Positioning System, lidar, radar information, or prior (map-based) knowledge To the extent of our knowledge, this is the first work to use official Institute of Transportation Engineers (US) and British Standards Institute (European Union) standards for defining traffic light colors, as well as integrating a number of fail-safe mechanisms designed to prevent erroneous detection The algorithm can be easily ported over to an embedded smart camera platform and used as a windshield-mounted driver-assistance device by individuals with CVD The system can accurately identify the status of the light at 400 ft away from the intersection, reliably detecting solid, faulty, arrow, and high-visibility signal lights Over 50 h of video (over 2000 intersections) were tested with the system, containing intersections with one to four traffic lights, governing different lanes of traffic, with 975% accuracy of solid light detection

Portable infrared camera

Abstract: An infrared camera provided with a rotating lens. The exterior of the camera is also provided with a touch screen display as well as a switch device such as a 5-way switch, controlling many of the functions of the infrared camera. The rotation of the lens would allow an operator to view different objects while maintaining a single position, allowing the operator to view the material projected on the display very easily. A trigger would be used to capture a particular infrared image and to save this image as well as to transmit it, at a later time, to a personal computer.