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Proceedings ArticleDOI

A real-time color-based object tracking and occlusion handling using ARM cortex-A7

TL;DR: This work has proposed a robust Color-based algorithm to track the object and handle occlusion in real time domain and results showed run time performance, efficiency and accuracy inreal time environment.
Abstract: In computer vision application object tracking is a challenging problem. Illumination and occlusion are major constraints observed in object tracking. We are focusing on object tracking with partial or full occlusion. Object tracking is done using features like colors and contours. We have proposed a robust Color-based algorithm to track the object and handle occlusion in real time domain. In our algorithm, HSV color model is used and HSV range of the color object to be tracked is selected. Required object area is identified and contour is formed accordingly to track the object. Proposed algorithm is implemented on ARM Cortex-A7 using Open Source Computer Vision (OpenCV) and Linux-embedded platform. The experiment is done using generated real life database and standard unusual crowd activity database. Results showed run time performance, efficiency and accuracy in real time environment.
Citations
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Proceedings ArticleDOI
01 May 2017
TL;DR: Using the proposed technique, the sorting robotic arm system can distinguish and sort different objects successfully with properly tuned parameters for both machine vision and 3D mobility of the robotic arm.
Abstract: Sorting is a labor intense process With machines that can recognize objects, it is possible to automate the sorting process In this paper, we present a robotic sorting arm based on color recognition technique In this system, when a new frame is captured by the camera, the object will be detected using color-base image processing technique The position of the object in real-world will be calculated by its mass center in image Using Inverse Kinematics algorithms, the control input for the robotic arm will be calculated and then sent to Arduino microcontroller Then, the microcontroller will drive the motors on the robotic arm to sort and position the objects according to their color Using the proposed technique, the sorting robotic arm system can distinguish and sort different objects successfully with properly tuned parameters for both machine vision and 3D mobility of the robotic arm

9 citations


Cites methods from "A real-time color-based object trac..."

  • ...The result of this color detection method can be seen in Figure 9 [4]....

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Book ChapterDOI
05 Sep 2018
TL;DR: An application is made to perform looming detection and to detect imminent collision on a system-on-chip field-programmable gate array (SoC- FPGA) hardware.
Abstract: Real time classification of objects using computer vision techniques are becoming relevant with emergence of advanced perceptions systems required by, surveillance systems, industry 4.0 robotics and agricultural robots. Conventional video surveillance basically detects and tracks moving object whereas there is no indication of whether the object is approaching or receding the camera (looming). Looming detection and classification of object movements aids in knowing the position of the object and plays a crucial role in military, vehicle traffic management, robotics, etc. To accomplish real-time object trajectory classification, a contour tracking algorithm is necessary. In this paper, an application is made to perform looming detection and to detect imminent collision on a system-on-chip field-programmable gate array (SoC- FPGA) hardware. The work presented in this paper was designed for running in Robotic platforms, Unmanned Aerial Vehicles, Advanced Driver Assistance System, etc. Due to several advantages of SoC-FPGA the proposed work is performed on the hardware. The proposed work focusses on capturing images, processing, classifying the movements of the object and issues an imminent collision warning on-the-fly. This paper details the proposed software algorithm used for the classification of the movement of the object, simulation of the results and future work.

3 citations

Proceedings ArticleDOI
01 Aug 2018
TL;DR: An improved Apriltag-based tracking algorithm running on a low cost embedded mobile robot with Raspberry Pi3 is proposed and a secondary detection algothm is designed based on Apriltsag’s recognition principle to improve the locating and tracking rate.
Abstract: Moving object locating and tracking are always the challenges in computer vision, especially in autonomous mobile robot vision. Due to the relative movement between the object and the robot as well as the image overexposure, the images are easily got blur, or worse, the object is loss and unable to be tracked. High-performance hardware and complex intelligent algorithms can make up these abuses in some degree, however, these solutions are of high cost and unable to be realized in consumer robots. Addressing on this problem, an improved Apriltag-based tracking algorithm running on a low cost embedded mobile robot with Raspberry Pi3 is proposed. Dynamic downsampling algorithm is first proposed to improve the real-time performance of the traditional Apriltag-based tracking algorithm. The dynamic downsampling coefficient is then studied through experiments and fitting technology. Then the relative velocity is also taken into account to enhance the downsampling accuracy. Image enhancement based on histogram equalization is used to reduce the image blur caused by downsampling and the relative motion. Finally, a secondary detection algothm is designed based on Apriltag’s recognition principle to improve the locating and tracking rate.

Cites background from "A real-time color-based object trac..."

  • ...[3] proposed a real-time color-based object tracking algorithm for ARM Cortex-A7....

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Journal ArticleDOI
TL;DR: The NSSD-DT method is developed, which allows us to track a target in a robust way and effectively overcomes the problems of geometrical deformation of the target, partial occlusion and allows recovery after the target leaves the field of view.
Abstract: In this work, we developed the NSSD-DT method, which allows us to track a target in a robust way. This method effectively overcomes the problems of geometrical deformation of the target, partial occlusion and allows recovery after the target leaves the field of view. The originality of our algorithm is based on a new model, which does not depend on a probabilistic process and does not require data-based beforehand. Experimental results on several difficult video sequences have proven performance benefits. The algorithm is implemented on a BCS 2835 system based on a quad core ARM processor, it is also compared to the software solution. NSSD-DT can be used in several applications such as video surveillance, active vision or industrial visual servoing.

Cites methods from "A real-time color-based object trac..."

  • ...Tracking objects with partial or complete occlusion using features such as colors and contours based on the HSV color model by [4]....

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References
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Proceedings ArticleDOI
23 Jun 2014
TL;DR: The contribution of color in a tracking-by-detection framework is investigated and an adaptive low-dimensional variant of color attributes is proposed, suggesting that color attributes provides superior performance for visual tracking.
Abstract: Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power. This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional variant of color attributes. Both quantitative and attribute-based evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24 % in median distance precision. Furthermore, we show that our approach outperforms state-of-the-art tracking methods while running at more than 100 frames per second.

1,499 citations


"A real-time color-based object trac..." refers methods in this paper

  • ...[2] have proposed an algorithm based on the adaptive color Attributes for visual object tracking....

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Book
05 Sep 2006
TL;DR: Comprehensive Real-World Guidance for Every Embedded Developer and Engineer brings together indispensable knowledge for building efficient, high-value, Linux-based embedded products: information that has never been assembled in one place before.
Abstract: Comprehensive Real-World Guidance for Every Embedded Developer and EngineerThis book brings together indispensable knowledge for building efficient, high-value, Linux-based embedded products: information that has never been assembled in one place before. Drawing on years of experience as an embedded Linux consultant and field application engineer, Christopher Hallinan offers solutions for the specific technical issues you're most likely to face, demonstrates how to build an effective embedded Linux environment, and shows how to use it as productively as possible.Hallinan begins by touring a typical Linux-based embedded system, introducing key concepts and components, and calling attention to differences between Linux and traditional embedded environments. Writing from the embedded developer's viewpoint, he thoroughly addresses issues ranging from kernel building and initialization to bootloaders, device drivers to file systems.Hallinan thoroughly covers the increasingly popular BusyBox utilities; presents a step-by-step walkthrough of porting Linux to custom boards; and introduces real-time configuration via CONFIG_RT--one of today's most exciting developments in embedded Linux. You'll find especially detailed coverage of using development tools to analyze and debug embedded systems--including the art of kernel debugging. Compare leading embedded Linux processors Understand the details of the Linux kernel initialization process Learn about the special role of bootloaders in embedded Linux systems, with specific emphasis on U-Boot Use embedded Linux file systems, including JFFS2--with detailed guidelines for building Flash-resident file system images Understand the Memory Technology Devices subsystem for flash (and other) memory devices Master gdb, KGDB, and hardware JTAG debugging Learn many tips and techniques for debugging within the Linux kernel Maximize your productivity in cross-development environments Prepare your entire development environment, including TFTP, DHCP, and NFS target servers Configure, build, and initialize BusyBox to support your unique requirementsAbout the AuthorChristopher Hallinan, field applications engineer at MontaVista software, has worked for more than 20 years in assignments ranging from engineering and engineering management to marketing and business development. He spent four years as an independent development consultant in the embedded Linux marketplace. His work has appeared in magazines, including Telecommunications Magazine, Fiber Optics Magazine, and Aviation Digest.

63 citations


"A real-time color-based object trac..." refers background in this paper

  • ...It supports root file system which contains predefined files, directories and libraries [16]....

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Proceedings ArticleDOI
16 May 2014
TL;DR: A fog level detection method based on image HSV color histogram that can make qualitative judgments on foggy days quickly and the qualitative detection results are relatively good is proposed.
Abstract: As a direction in the development of computer vision, fog visibility detection is very important for traffic safety. Aiming at the visibility detection problem appearing in the highspeed road traffic, this paper proposes a fog level detection method based on image HSV color histogram. First, convert the background image color space from RGB color space to HSV color space. And then achieve the fog level detection by classifying fog weathers of different visibility level into different types using the image HSV color histogram features (including H, S, and V) in various weather conditions. The experimental results show that this method can make qualitative judgments on foggy days quickly and the qualitative detection results are relatively good.

26 citations


"A real-time color-based object trac..." refers background in this paper

  • ...Saturation and value are shown by distances along the axes [9]....

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  • ...HSV color space is denoted by the volume of Hue, Saturation and Value present in color space [8] [9]....

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  • ...It is cylindrical co-ordinate system (inverted hex-cone) [9]....

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Proceedings ArticleDOI
01 Dec 2010
TL;DR: A vision based moving Object Tracking system with Wireless Surveillance Camera which uses a color image segmentation and color histogram with background subtraction for tracking any objects in non-ideal environment is implemented.
Abstract: In this paper we implement a vision based moving Object Tracking system with Wireless Surveillance Camera which uses a color image segmentation and color histogram with background subtraction for tracking any objects in non-ideal environment. The implementation of the moving video objects can be based on any one of the tracking algorithms such as Template matching, Continuously Adaptive Mean Shift (CAMSHIFT), SIFT, Mean Shift, SIFT, Cross correlation algorithm is presented by optimizing the kernel variants by adjusting the HSV value for various environmental conditions. The object occlusions are also removed by calculating the minimal distance between the two objects using Bhattacharya coefficients and it is robust to changes in shape with complete occlusion. The object to be tracked can also be classified using HAAR classifier through machine learning. A software approach for real time implementation of moving object tracking is done through MATLAB.

12 citations


"A real-time color-based object trac..." refers methods in this paper

  • ...[7] have described color image segmentation method using HAAR classifiers for vision based moving object tracking....

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Proceedings ArticleDOI
30 Apr 2015
TL;DR: The ability to recognise objects and humans, to describe their actions and interactions from information acquired by sensors using absolute difference motion detection technique is described.
Abstract: Surveillance is the monitoring of the behavior, activities, or other changing information, usually of people for the purpose of influencing, managing, directing, or protecting them. As security is becoming the primary concern of society and hence having a security system is becoming a big requirement. Video surveillance plays a vital role in security systems. This paper describes the ability to recognise objects and humans, to describe their actions and interactions from information acquired by sensors using absolute difference motion detection technique. Real-time implementation is achieved by using a Global System for Mobile Communication (GSM) modem for SMS (Short Message Service) notification. The ablity of tracking and recognition of the visual device was implemented using OpenCVTM for displaying an output. The detected objects motion is being captured and stored in HDD.

7 citations


"A real-time color-based object trac..." refers background or methods in this paper

  • ...Hence the area of foreground pixel shrink in size [12]....

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  • ...thinning and thickening of the object [12]....

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  • ...Evaluation of each pixel intensity value with respect to a threshold is used to improve subtraction [12]....

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  • ...It expands the areas of foreground pixel [12]....

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