Search results for "smart camera"
showing 10 items of 30 documents
Smart cameras on a chip: using complementary metal-oxide-semiconductor (CMOS) image sensors to create smart vision chips
2020
Abstract: In this chapter, we introduce the fundamental concept of smart cameras on a chip or smart vision chips that simultaneously integrate the same die image capture capability and highly complex image processing. Successive technology scaling has made possible the integration of specific processing elements designed at chip level, at column level or at pixel level. To illustrate this continuous evolution, we survey three different categories of vision chips, exploring first the pioneering works on artificial retinas, then describing the most significant computational chips, and finally presenting the most recent image processing chips able to perform complex algorithms at a high frame …
FPGA-based smart camera : industrial applications
2013
International audience; For the last two decades and still today, smart cameras offer innovative solutions for industrial vision applications. This kind of system associates a flexible image acquisition with high-speed processing possibilities. Many smart camera designs are based on FPGA components to obtain these two features. Indeed, the FPGA enables the CMOS sensor to be controlled and therefore to propose a configurable acquisition according to the application constraints (i.e. dynamic windowing). The configurable structure of a FPGA represents a key advantage for modifying the embedded processing (even on-the-fly using dynamic reconfiguration). Meanwhile, FPGA components offer a large …
Efficient smart-camera accelerator: A configurable motion estimator dedicated to video codec
2013
Smart cameras are used in a large range of applications. Usually the smart cameras transmit the video or/and extracted information from the video scene, frequently on compressed format to fit with the application requirements. An efficient hardware accelerator that can be adapted and provide the required coding performances according to the events detected in the video, the available network bandwidth or user requirements, is therefore a key element for smart camera solutions. We propose in this paper to focus on a key part of the compression system: motion estimation. We have developed a flexible hardware implementation of the motion estimator based on FPGA component, fully compatible with…
Use of wavelet for image processing in smart cameras with low hardware resources
2013
International audience; Images from embedded sensors need digital processing to recover high-quality images and to extract features of a scene. Depending on the properties of the sensor and on the application, the designer fits together different algorithms to process images. In the context of embedded devices, the hardware supporting those applications is very constrained in terms of power consumption and silicon area. Thus, the algorithms have to be compliant with the embedded specifications i.e. reduced computational complexity and low memory requirements. We investigate the opportunity to use the wavelet representation to perform good quality image processing algorithms at a lower compu…
Smart camera design for intensive embedded computing
2005
Computer-assisted vision plays an important role in our society, in various fields such as personal and goods safety, industrial production, telecommunications, robotics, etc. However, technical developments are still rare and slowed down by various factors linked to sensor cost, lack of system flexibility, difficulty of rapidly developing complex and robust applications, and lack of interaction among these systems themselves, or with their environment. This paper describes our proposal for a smart camera with real-time video processing capabilities. A CMOS sensor, processor and, reconfigurable unit associated in the same chip will allow scalability, flexibility, and high performance.
Real-time High Dynamic Range based on Multiple Non Destructive ReadOut during a Single Exposure
2017
This paper presents a new method based on Non Destructive Readout (NDRO) to improve multi-exposure High Dynamic Range (HDR) Imaging. A sequence of Low-Dynamic Range (LDR) images can then be acquired during a single exposure. The concept enables the latency between LDR images to be removed as well as the intrinsic ghost artifacts observed using state-of-art HDR systems based on multi-exposures. The method has been applied to improve the performances of HDR sensor based on logarithmic pixels. Using the NDRO method, a Short Wave InfraRed (SWIR) camera has been designed to produce HDR IR videos. A real-time HDR video stream generation is achieved based on GPU implantation.
A 1.3 megapixel FPGA-based smart camera for high dynamic range real time video
2013
International audience; A camera is able to capture only a part of a high dynamic range scene information. The same scene can be fully perceived by the human visual system. This is true especially for real scenes where the difference in light intensity between the dark areas and bright areas is high. The imaging technique which can overcome this problem is called HDR (High Dynamic Range). It produces images from a set of multiple LDR images (Low Dynamic Range), captured with different exposure times. This technique appears as one of the most appropriate and a cheap solution to enhance the dynamic range of captured environments. We developed an FPGA-based smart camera that produces a HDR liv…
Machine Learning VS Transfer Learning - Smart Camera Implementation for Face Authentication
2018
The aim of this paper is to highlight differences between classical machine learning and transfer learning applied to low cost real-time face authentication. Furthermore, in an access control context, the size of biometric data should be minimized so it can be stored on a remote personal media. These constraints have led us to compare only lightest versions of these algorithms. Transfer learning applied on Mobilenet v1 raises to 85% of accuracy, for a 457Ko model, with 3680s and 1.43s for training and prediction tasks. In comparison, the fastest integrated method (Random Forest) shows accuracy up to 90% for a 7,9Ko model, with a fifth of a second to be trained and a hundred of microseconds …
Smart camera based on an Embedded HW/SW Co-Processor
2008
Abstract This paper describes an image acquisition and a processing system based on a new coprocessor architecture designed for CMOS sensor imaging. The system exploits the full potential CMOS selective access imaging technology because the coprocessor unit is integrated into the image acquisition loop. The acquisition and coprocessing architecture are compatible with the majority of CMOS sensors. It enables the dynamic selection of a wide variety of acquisition modes as well as the reconfiguration and implementation of high-performance image preprocessing algorithms (calibration, filtering, denoising, binarization, pattern recognition). Furthermore, the processing and data transfer, from t…
Enabling Technologies on Hybrid Camera Networks for Behavioral Analysis of Unattended Indoor Environments and Their Surroundings
2008
This paper presents a layered network architecture and the enabling technologies for accomplishing vision-based behavioral analysis of unattended environments. Specifically the vision network covers both the attended environment and its surroundings by means of multi-modal cameras. The layer overlooking at the surroundings is laid outdoor and tracks people, monitoring entrance/exit points. It recovers the geometry of the site under surveillance and communicates people positions to a higher level layer. The layer monitoring the unattended environment undertakes similar goals, with the addition of maintaining a global mosaic of the observed scene for further understanding. Moreover, it merges …