Development Tools

Development Tools for Embedded Vision

ENCOMPASSING MOST OF THE STANDARD ARSENAL USED FOR DEVELOPING REAL-TIME EMBEDDED PROCESSOR SYSTEMS

The software tools (compilers, debuggers, operating systems, libraries, etc.) encompass most of the standard arsenal used for developing real-time embedded processor systems, while adding in specialized vision libraries and possibly vendor-specific development tools for software development. On the hardware side, the requirements will depend on the application space, since the designer may need equipment for monitoring and testing real-time video data. Most of these hardware development tools are already used for other types of video system design.

Both general-purpose and vender-specific tools

Many vendors of vision devices use integrated CPUs that are based on the same instruction set (ARM, x86, etc), allowing a common set of development tools for software development. However, even though the base instruction set is the same, each CPU vendor integrates a different set of peripherals that have unique software interface requirements. In addition, most vendors accelerate the CPU with specialized computing devices (GPUs, DSPs, FPGAs, etc.) This extended CPU programming model requires a customized version of standard development tools. Most CPU vendors develop their own optimized software tool chain, while also working with 3rd-party software tool suppliers to make sure that the CPU components are broadly supported.

Heterogeneous software development in an integrated development environment

Since vision applications often require a mix of processing architectures, the development tools become more complicated and must handle multiple instruction sets and additional system debugging challenges. Most vendors provide a suite of tools that integrate development tasks into a single interface for the developer, simplifying software development and testing.

“Image Signal Processing Optimization for Object Detection,” a Presentation from Nextchip

Young-Jun Yoo, Executive Vice President at Nextchip, presents the “Image Signal Processing Optimization for Object Detection” tutorial at the May 2024 Embedded Vision Summit. This talk delves into the challenges and optimization strategies in image signal processing (ISP) for enhancing object detection in advanced driver-assistance systems (ADAS). Through real-world examples,… “Image Signal Processing Optimization for

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Understanding Spatial Noise and Its Reduction Methods Using Convolution

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Convolution is a mathematical operation used in image processing to apply filters to images. These filters are used for spatial noise reduction in images with variations or irregularities in the pixel values that are unrelated

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“Maximize Your AI Compatibility with Flexible Pre- and Post-processing,” a Presentation from Flex Logix

Jayson Bethurem, Vice President of Marketing and Business Development at Flex Logix, presents the “Maximize Your AI Compatibility with Flexible Pre- and Post-processing” tutorial at the May 2024 Embedded Vision Summit. At a time when IC fabrication costs are skyrocketing and applications have increased in complexity, it is important to… “Maximize Your AI Compatibility with

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“Addressing Tomorrow’s Sensor Fusion and Processing Needs with Cadence’s Newest Processors,” a Presentation from Cadence

Amol Borkar, Product Marketing Director at Cadence, presents the “Addressing Tomorrow’s Sensor Fusion and Processing Needs with Cadence’s Newest Processors” tutorial at the May 2024 Embedded Vision Summit. From ADAS to autonomous vehicles to smartphones, the number and variety of sensors used in edge devices is increasing: radar, LiDAR, time-of-flight… “Addressing Tomorrow’s Sensor Fusion and

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“Temporal Event Neural Networks: A More Efficient Alternative to the Transformer,” a Presentation from BrainChip

Chris Jones, Director of Product Management at BrainChip, presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit. The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent… “Temporal Event Neural Networks: A

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How Edge Devices Can Help Mitigate the Global Environmental Cost of Generative AI

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Exploring the role of edge devices in reducing energy consumption and promoting sustainability in AI systems The economic value of generative artificial intelligence (AI) to the world is immense. Research from McKinsey estimates that generative AI could add the

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“Silicon Slip-ups: The Ten Most Common Errors Processor Suppliers Make (Number Four Will Amaze You!),” a Presentation from BDTI

Phil Lapsley, Co-founder and Vice President of BDTI, presents the “Silicon Slip-ups: The Ten Most Common Errors Processor Suppliers Make (Number Four Will Amaze You!)” tutorial at the May 2024 Embedded Vision Summit. For over 30 years, BDTI has provided engineering, evaluation and advisory services to processor suppliers and companies… “Silicon Slip-ups: The Ten Most

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