855 research outputs found
RSGM: Real-time Raster-Respecting Semi-Global Matching for Power-Constrained Systems
Stereo depth estimation is used for many computer vision applications. Though
many popular methods strive solely for depth quality, for real-time mobile
applications (e.g. prosthetic glasses or micro-UAVs), speed and power
efficiency are equally, if not more, important. Many real-world systems rely on
Semi-Global Matching (SGM) to achieve a good accuracy vs. speed balance, but
power efficiency is hard to achieve with conventional hardware, making the use
of embedded devices such as FPGAs attractive for low-power applications.
However, the full SGM algorithm is ill-suited to deployment on FPGAs, and so
most FPGA variants of it are partial, at the expense of accuracy. In a non-FPGA
context, the accuracy of SGM has been improved by More Global Matching (MGM),
which also helps tackle the streaking artifacts that afflict SGM. In this
paper, we propose a novel, resource-efficient method that is inspired by MGM's
techniques for improving depth quality, but which can be implemented to run in
real time on a low-power FPGA. Through evaluation on multiple datasets (KITTI
and Middlebury), we show that in comparison to other real-time capable stereo
approaches, we can achieve a state-of-the-art balance between accuracy, power
efficiency and speed, making our approach highly desirable for use in real-time
systems with limited power.Comment: Accepted in FPT 2018 as Oral presentation, 8 pages, 6 figures, 4
table
An Experimental Study on Pitch Compensation in Pedestrian-Protection Systems for Collision Avoidance and Mitigation
This paper describes an improved stereovision system for the anticipated detection of car-to-pedestrian accidents. An improvement of the previous versions of the pedestrian-detection system is achieved by compensation of the camera's pitch angle, since it results in higher accuracy in the location of the ground plane and more accurate depth measurements. The system has been mounted on two different prototype cars, and several real collision-avoidance and collision-mitigation experiments have been carried out in private circuits using actors and dummies, which represents one of the main contributions of this paper. Collision avoidance is carried out by means of deceleration strategies whenever the accident is avoidable. Likewise, collision mitigation is accomplished by triggering an active hood system
Advances in Stereo Vision
Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints
An Architecture for High-throughput and Improved-quality Stereo Vision Processor
This paper presents the VLSI architecture to achieve high-throughput and
improved-quality stereo vision for real applications. The stereo vision processor
generates gray-scale output images with depth information from input images taken by
two CMOS Image Sensors (CIS). The depth estimator using the sum of absolute
differences (SAD) algorithm as stereo matching technique is implemented on hardware
by exploiting pipelining and parallelism. To produce depth maps with improved-quality
at real-time, pre- and post-processing units are adopted, and to enhance the adaptability
of the system to real environments, special function registers (SFRs) are assigned to
vision parameters. The design using 0.18um standard CMOS technology can operate at
120MHz clock, achieving over 140 frames/sec depth maps with 320 by 240 image size
and 64 disparity levels. Experimental results based on images taken in real world and
the Middlebury data set will be presented. Comparison data with existing hardware
systems and hardware specifications of the proposed processor will be given
Stereoscopic hand-detection system based on FPGA
Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major de Telecomunicações). Faculdade de Engenharia. Universidade do Porto. 200
MINIMIZATION OF RESOURCE UTILIZATION FOR A REAL-TIME DEPTH-MAP COMPUTATIONAL MODULE ON FPGA
Depth-map algorithm allows camera system to estimate depth in many applications. The algorithm is computationally intensive and therefore more effective to be implemented on hardware such as the Field Programmable Gate Array (FPGA). However, the recurring issue in FPGA implementation is the resource limitation. The issue is normally resolved by modifying the algorithm. However, the issue can also be addressed by implementing hardware architectures without the need to modify the depth-map algorithm. In this thesis, five different depth-map processor architectures for the sum-of-absolute-difference (SAD) depth-map algorithm on FPGA at real-time were designed and implemented. Two resource minimization techniques were employed to address the resource limitation issues. Resource usage and performance of these architectures were compared. Memory contention and bandwidth constrain were resolved by using self-initiative memory controller, FIFOs and line buffers. Parallel processing was utilized to achieve high processing speed at low clock frequency. Memory-based line buffers were used instead of register-based line buffers to save 62.4% of logic element (LEs) used, but require some additional dedicated memory bits. A proper use of registers to replace repetitive subtractors saves 24.75% of LEs. The system achieves SAD performance of 295 mega pixel disparity per second (MPDS) for the architecture with 640x480 pixel image, 3x3 pixel window size, 32 pixel disparity range and 30 frames per second. The system achieves SAD performance of 590 MPDS for the 64 pixels disparity range architecture. The disparity matching module works at the frequency of 10 MHz and produces one pixel of result every clock cycle. The results are dense disparity images, suitable for high speed, low cost, low power applications
Design of a Real-time Image-based Distance Sensing System by Stereo Vision on FPGA
A stereo vision system is a robust method to sense the distance information in a scene. This research explores the stereo vision system from the fundamentals of stereo vision and the
computer stereo vision algorithm to the final implementation of the system on a FPGA chip. In a stereo vision system, images are captured by a pair of stereo image sensors. The distance information
can be derived from the disparities between the stereo image pair, based on the theory of binocular geometry. With the increasing focus on 3D vision, stereo vision is becoming a hot topic in the areas of computer games, robot vision and medical applications. Particularly, most stereo vision systems are expected to be used in real-time applications.
In this thesis, several stereo correspondence algorithms that determine the disparities between stereo image pair are examined. The algorithms can be categorized into global stereo algorithms and local stereo algorithms depending on the optimization techniques. The global algorithms examined are the Dynamic Time Warp (DTW) algorithm and the DTW with quantization algorithm, while the local algorithms examined are the window based Sum of Squared Differences (SSD), Sum of Absolute Differences (SAD) and Census transform correlation algorithms. With analysis among them, the window based
SAD correlation algorithm is proposed for implementation on a FPGA platform.
The proposed algorithm is implemented onto an Altera DE2 board featuring an Altera Cyclone II 2C35 FPGA. The implemented module of the algorithm is simulated using ModelSim-Altera to verify the correctness of its functionality. Along with a pair of stere image sensors and a LCD monitor, a stereo vision system is built. The entire system realizes a real-time video frame rate of 16.83 frames per second with an image resolution of 640 by 480 and produces disparity maps in which the objects are clearly distinguished by their relative distance information
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