ASSET-2: Real-Time Motion Segmentation and Shape Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implementation of single precision floating point square root on FPGAs
FCCM '97 Proceedings of the 5th IEEE Symposium on FPGA-Based Custom Computing Machines
Mapping a Single Assignment Programming Language to Reconfigurable Systems
The Journal of Supercomputing
VisionBug: A Hexapod Robot Controlled by Stereo Cameras
Autonomous Robots
Compiling SA-C Programs to FPGAs: Performance Results
ICVS '01 Proceedings of the Second International Workshop on Computer Vision Systems
An optimal algorithm for minimizing run-time reconfiguration delay
ACM Transactions on Embedded Computing Systems (TECS)
Collaborative and reconfigurable object tracking
The Journal of Supercomputing
On-Road Vehicle Detection: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconfiguration in network of embedded systems: Challenges and adaptive tracking case study
Journal of Embedded Computing - Real-Time and Embedded Computing Systems
Towards an Embedded Visuo-Inertial Smart Sensor
International Journal of Robotics Research
Embedded active vision system based on an FPGA architecture
EURASIP Journal on Embedded Systems
Computer Vision Based Autonomous Navigation for Pin-Point Landing Robotic Spacecraft on Asteroids
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
Visual odometry with effective feature sampling for untextured outdoor environment
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Real-time feature point tracking at 1000 fps
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Fast image motion segmentation for surveillance applications
Image and Vision Computing
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We have designed and implemented a system for real-time detection of 2-D features on a reconfigurable computer based on Field Programmable Gate Arrays (FPGA's). We envision this device as the front-end of a system able to track image features in real-time control applications like autonomous vehicle navigation. The algorithm employed to select good features is inspired by Tomasi and Kanade's method. Compared to the original method, the algorithm that we have devised does not require any floating point or transcendental operations, and can be implemented either in hardware or in software. Moreover, it maps efficiently into a highly pipelined architecture, well suited to implementation in FPGA technology. We have implemented the algorithm on a low-cost reconfigurable computer and have observed reliable operation on an image stream generated by a standard NTSC video camera at 30 Hz.