Swallow Incubate Co., Ltd. List of News Articles

Swallow Incubate Co., Ltd. will participate in the "96th Tsukuba Research Seed/Venture Technology Presentation" (Theme: Cutting-edge Measurement Technology - Seeing) hosted by the Tsukuba Research Support Center and Tsukuba University on December 11, 2026 (Friday). Our representative director, Toshikazu Ohno, will present on the topic "Protecting and Measuring with the Eyes - AI for Face Impersonation Detection and Blink Detection," introducing two technologies that read the state of the face and eyes from camera footage, as well as how to incorporate them into products and services. ■ Event Overview - Date and Time: December 11, 2026 (Friday) 14:00 - 16:00 - Venue: Tsukuba Research Support Center Training Room A / Online (Zoom Webinar) - Participation Fee: Free - Organized by: Tsukuba Research Support Center / Tsukuba University There will be time for business card exchanges at the on-site venue, and online participants can also apply for individual meetings at a later date. Please refer to the news release in the related links for application details.

We have released a "trial version app (browser version)" that allows you to freely test the "blinking detection technology" developed using joint patent technology with Panasonic, directly in your browser. No application, installation, or membership registration is required. It measures blinking for 30 seconds using your PC's built-in camera or your smartphone's camera, displaying the number of blinks, the rate per minute, the duration of closed eyes (average and longest), and the intervals between blinks in real-time. The camera footage is processed within the browser, and neither the video nor the measurement results are sent externally. Additionally, we have started online sales of the "blinking detection app (Windows version)" that allows unlimited measurements for research and verification purposes. It supports recording and CSV output, with prices set at 33,000 yen for general users and 16,500 yen for academic institutions (tax included, per license, one-time purchase). The camera input version and the file input version are sold separately. For integration into products and services, we also offer the "blinking detection SDK" (with a one-month free trial version available).

We have started offering the latest version 1.1.0 of the "Blink Detection SDK," which detects blinking from the state of eye opening and closing using only a PC's webcam or a smartphone camera. The face detection model has been updated to the lightweight and fast YuNet, and it supports usage from C#/.NET (verified to work with .NET 8). The same version is provided across four platforms: Windows, Linux, iOS, and Android, and it includes eight sample applications for each platform. It can process quickly using only the CPU without the need for a GPU, making it useful for integration into products and services for features like eye strain prevention alerts and touchless operations. A one-month free trial version (SDK/Windows app/smartphone app) is available.

The facial recognition system requires both facial recognition to verify "whether it matches the registered individual" and spoof detection to confirm "whether the person in front of the camera is a real human and not a photo or screen." We are pleased to announce that our company has started offering a facial recognition SDK as an add-on to the "spoof detection SDK" used in major medical institutions and in entry/exit management and attendance management settings. ■ What you can do with the set - By simply passing the same camera feed to both SDKs, you can integrate both identity verification and biometric detection. - In our validation, we were able to detect all face photos and smartphone screens that would pass through facial recognition alone when combined with spoof detection. - Facial verification accuracy: 99.37% (public benchmark LFW, in-house evaluation) - Compatible with Windows / Linux / iOS / Android We offer a one-month free trial version. For more details, please refer to the news release in the related links.

Swallow Incubate Co., Ltd. has started providing the latest version 2.4.0 of its "Impersonation Detection SDK," which detects "impersonation" using photos, smartphone screens, and printed materials during face recognition and identity verification, starting September 29, 2026. In this version, the core fake detection models (for landscape and portrait images) have been updated to enhance generalization performance, allowing for stable detection against unknown shooting environments and unknown attack patterns. Evaluation using approximately 1 million frames of in-house verification data has confirmed a detection accuracy of 99.9% (in-house evaluation). The detection engine for the "Impersonation Detection API" available on the cloud (AWS Marketplace) has also been updated to version 2.4.0. There are no changes to the pricing plans. A trial version of the SDK (Windows / Linux / iOS / Android) is available for free for one month.

Swallow Incubate Co., Ltd. has published a series of 10 technical articles on the determination of impersonation (liveness detection) in facial recognition systems, accompanied by implementation code and actual measurement values, on the "Swallow Incubate Technical Blog." All articles are available for free. Facial recognition is a technology that determines "who someone is," but it does not assess "whether that face is alive." When a standard facial recognition system is implemented using OpenCV and a printed photo of the person is presented, it can pass as the actual person. This series is structured into four parts for those responsible for the design, implementation, and procurement of facial recognition systems: 1. Facial recognition alone cannot prevent impersonation (actual measurements of implementation and photo-based bypass). 2. Types of attacks and how to interpret accuracy (differences between FAR/FRR and APCER/BPCER; limitations of three simple liveness methods). 3. Actual measurement information necessary for consideration of implementation (design for on-premises, closed networks, and embedded systems; face detection at 13.5 fps on Raspberry Pi 5; SDK integration in 23 lines of C++/22 lines of C#; retrofitting to existing systems). 4. A checklist of 12 design items. Reproduction procedures for attacks are not included. For details, please refer to the related links.

Swallow Incubate Co., Ltd. made its Liveness Detection API generally available on July 28, 2026 through AWS Marketplace, serving customers in Japan and worldwide. The API delivers over the cloud the same fake-detection engine as our Liveness Detection SDK, which is deployed at more than 40 sites across Japan. No SDK integration is needed: a single REST API call adds a live-or-fake decision to an existing face recognition or eKYC (online identity verification) flow. Liveness detection identifies presentation attacks - attempts to defeat face recognition by presenting a photograph, a smartphone screen or a printed image to the camera. The technology comprises fake detection, which decides from a single still frame, and action detection, which asks the user to perform randomized actions such as turning the head or blinking. This API provides fake detection, which requires only one still image. As of the end of June 2026, our liveness detection technology is deployed at more than 40 sites across Japan, in applications including authentication solutions for major medical institutions, access control terminals and attendance management terminals. Six plans, including a free tier of 50 calls per month, are available on AWS Marketplace.

Swallow Incubate Co., Ltd. has launched the Swallow Incubate Tech Blog, a technical site covering the implementation of liveness detection, face recognition and image processing. Developers who design and build face recognition systems have told us they lack the information needed to judge which technology to choose and what it can and cannot do. In particular, face recognition and liveness detection (protection against presentation attacks) are separate technologies - a point that is often recognised only at the implementation stage. The blog publishes that material. Our editorial rule is that every article carries implementation code and measured results. It is organised into three categories: Liveness Detection, OpenCV for C++, and OpenCV for C#.

Swallow Incubate Co., Ltd. announces its security operations for our website (swallow-incubate.com). We run an automated vulnerability scan every month with "Onamae.com Net de Shindan," whose scanning engine is provided by GMO Cybersecurity by Ierae, Inc. Having met the required criteria, we now display their Cyber Attack Countermeasure Site Seal on the site. Swallow Incubate provides Liveness Detection (Anti-Spoofing) Technology, which detects spoofing attempts against face recognition. As a company whose technology underpins identity verification, we regard continuous checks of our own website as essential, and we will continue them as part of our ongoing work toward ISO/IEC 27001 (ISMS) certification.

We have started providing the "Liveness Detection SDK ver. 2.3.0". Built on technology jointly patented with Panasonic, our Liveness Detection SDK is deployed at more than 40 sites across Japan. This version improves fake-detection accuracy and face-position detection accuracy, updates the OpenCV library, and adds official support for C# (.NET 8). In an internal evaluation using approximately 1 million frames, the detection accuracy reached 99.99%. https://bio-check.pas-ta.io/