Khaleghi et al., 2008 - Google Patents
An improved real-time miniaturized embedded stereo vision system (MESVS-II)Khaleghi et al., 2008
View PDF- Document ID
- 12323197878002916390
- Author
- Khaleghi B
- Ahuja S
- Wu Q
- Publication year
- Publication venue
- 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
External Links
Snippet
In this paper we describe a fully integrated, real-time, miniaturized embedded stereo vision system (MESVS-II), which fits within 5times5cm and consumes very low power. This is a significant improvement over the original MESVS-I system in terms of performance, quality …
- 238000005457 optimization 0 abstract description 13
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/20—Processor architectures; Processor configuration, e.g. pipelining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F12/00—Accessing, addressing or allocating within memory systems or architectures
- G06F12/02—Addressing or allocation; Relocation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/76—Architectures of general purpose stored programme computers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Humenberger et al. | A fast stereo matching algorithm suitable for embedded real-time systems | |
Hernandez-Juarez et al. | Embedded real-time stereo estimation via semi-global matching on the GPU | |
Zhu et al. | Euphrates: Algorithm-soc co-design for low-power mobile continuous vision | |
Khaleghi et al. | An improved real-time miniaturized embedded stereo vision system (MESVS-II) | |
Park et al. | Real-time 3D registration using GPU | |
Ding et al. | Real-time stereo vision system using adaptive weight cost aggregation approach | |
Hofmann et al. | A scalable high-performance hardware architecture for real-time stereo vision by semi-global matching | |
Boikos et al. | A high-performance system-on-chip architecture for direct tracking for SLAM | |
Cao et al. | Robust bundle adjustment for large-scale structure from motion | |
Piccinelli et al. | UniDepth: Universal Monocular Metric Depth Estimation | |
Cambuim et al. | Hardware module for low-resource and real-time stereo vision engine using semi-global matching approach | |
Boikos et al. | A scalable fpga-based architecture for depth estimation in slam | |
Eyvazpour et al. | Hardware implementation of SLAM algorithms: a survey on implementation approaches and platforms | |
Duan et al. | RGB-Fusion: Monocular 3D reconstruction with learned depth prediction | |
Gkeka et al. | Reconfigurable system-on-Chip architectures for robust visual SLAM on humanoid robots | |
Anguita et al. | Optimization strategies for high-performance computing of optical-flow in general-purpose processors | |
Chen et al. | An FPGA-based RGBD imager | |
Camellini et al. | 3DV—An embedded, dense stereovision-based depth mapping system | |
Miao et al. | Pseudo-lidar for visual odometry | |
Li et al. | Eventor: an efficient event-based monocular multi-view stereo accelerator on FPGA platform | |
Igual et al. | Robust motion estimation on a low-power multi-core DSP | |
Zhang et al. | DSP-based traffic target detection for intelligent transportation | |
Sulzbachner et al. | An optimized silicon retina stereo matching algorithm using time-space correlation | |
Liu et al. | SURFEX: A 57fps 1080P resolution 220mW silicon implementation for simplified speeded-up robust feature with 65nm process | |
Khaleghi et al. | A new miniaturized embedded stereo-vision system (MESVS-I) |