Event-Based Vision Sensors Patents: Who Leads, Trends 2026
- 64.0% concentration. The top 5 of 54 ranked assignees hold 178 of the 278 records in scope — filing here is dominated by a small group, not a fragmented field.
- Filing has cooled from its 2020 peak. Activity peaked at 46 records in 2020 and moved from 29 in 2021 to 23 in 2024, a -21% change over that span, before the most recent partial years.
- H04N and G06T dominate the claim space. 53.2% of records touch pictorial-communication classes and 42.8% touch image-data processing, leaving positioning and radar-fusion classes comparatively open.
Filing growth compares 2021 (29 records) with 2024 (23) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 278 records in scope (CR5), not by the ranked leaders only.
What the patent record shows about event-based vision sensing
Event-based vision sensors, often called dynamic vision sensors, report per-pixel brightness changes asynchronously rather than capturing full frames on a clock. The 278 records in scope span 2015 through the current data cut-off and cluster around claims on contrast threshold tuning, event rate control, and fusion of event streams with conventional frame or depth data. The filing pattern is not evenly spread: a small set of assignees accounts for the majority of activity, and the technical claims themselves sit heavily inside pictorial-communication and image-processing classifications rather than in sensor-optics classes.
Patent families, rather than raw publication counts, give the fairer read on this field because a single invention can generate several continuations or be filed again in multiple jurisdictions. Because publication typically lags filing by around 18 months, the most recent one or two years in any trend chart will always look thinner than they eventually turn out to be — that effect explains part of the tail-off after 2024, not necessarily a real drop in inventive activity.
Filing trend and technology composition
Two views of the same 278-record dataset: how filing activity has moved year over year, and which IPC subclasses the claims actually sit in.
A 2020 peak followed by a real but partial decline
Filings ran from 31 in 2017 to a peak of 46 in 2020, then eased from 29 in 2021 to 23 in 2024 — a -21% change across that three-year window. Years after 2024 are still filling in under normal publication lag and should not be read as a continued fall.
Concentrated in pictorial communication and image processing
H04N (pictorial communication) covers 53.2% of the 278 records and G06T (image data processing) covers 42.8%; because records carry multiple IPC codes these shares overlap rather than sum to 100%. Positioning-adjacent classes like G01S (radar, sonar & positioning) at 7.2% and G01B (measuring length & dimensions) at 10.8% carry noticeably less claim density.
Shares are the percentage of the 278 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Event-Based Vision Sensors with Eureka
This page is one run against one query. Ask Eureka your own question about event-based vision sensors and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited records and a recent representative filing
US20240064424A1 — Dynamic vision sensor, method, and noise filtering circuit for a dynamic vision sensor
The filing describes a noise filtering circuit for a dynamic vision sensor that triggers a timeframe when a pixel group detects a first event, then evaluates whether a subsequent second event from the same pixel group falls inside that timeframe before forwarding it to arbitration logic — a mechanism aimed squarely at background activity noise.Filed by Sony Semiconductor Solutions Corporation, published 2024-02-22.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US10345447B1 | Dynamic vision sensor to direct lidar scanning | 183 |
| 2 | US20160093273A1 | Dynamic vision sensor with shared pixels and time division multiplexing for higher spatial resolution and bet… | 161 |
| 3 | US20190355169A1 | Semantic mapping for low-power augmented reality using dynamic vision sensor | 105 |
| 4 | US20180191972A1 | Dynamic vision sensor architecture | 105 |
| 5 | US20190045173A1 | Dynamic vision sensor and projector for depth imaging | 74 |
| 6 | US20190356849A1 | CMOS-assisted inside-out dynamic vision sensor tracking for low power mobile platforms | 67 |
| 7 | US20200026349A1 | System and method for hybrid eye tracker | 63 |
| 8 | US20170003121A1 | Method for Reconstructing A Surface Using Spatially Structured Light and A Dynamic Vision Sensor | 56 |
| 9 | WO2018122798A1 | Dynamic vision sensor architecture | 46 |
| 10 | US20190007678A1 | Generating heat maps using dynamic vision sensor events | 46 |
Citation counts reward older filings that have had more time to accumulate citations inside the searched corpus — treat this table as a map of influence on later filings, not a ranking of current technical importance.
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Browse MCP servers →What the concentration and composition numbers mean for filing strategy
The dataset points to a field where a handful of assignees hold most of the claim space, filing has passed its peak year but not necessarily its inventive activity, and the technology composition skews heavily toward signal and image processing over sensor optics.
Five assignees hold nearly two-thirds of the field
The top 5 of 54 ranked assignees account for 178 of the 278 records in scope, and the top 10 extend that to 82.0%. A new entrant filing broad claims on core event-readout architecture is filing into dense prior art held by a small group.
Activity has eased from its 2020 peak, not collapsed
The peak year so far is 2020 at 46 records. The move from 29 in 2021 to 23 in 2024 is a real -21% change, but years beyond 2024 are still incomplete under normal publication lag and should not be read as a cliff.
Claims cluster in signal handling, not sensor optics
Pictorial-communication and image-data-processing classes carry the bulk of claim density, while measuring and positioning classes (G01B, G01S) sit well below 15%. That gap is a reasonable place to look for less-crowded claim territory.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to event-based vision sensors, with the prior art for and against each one.
Assignee concentration and where the ranked leaders are pulling back
Filing in event-based vision sensing sits with a short list of large electronics and imaging companies, several of which show no activity in the latest tracked year — consistent with publication lag rather than an actual stop in R&D.
A single assignee leads by a wide margin
The leading assignee holds 63 records against 15 at fifth place and 7 at tenth — a steep drop-off that marks this as a leader-and-long-tail field rather than an evenly matched multi-way race.
Corporate group filings cluster tightly
The strongest co-assignee pairing in the dataset shares 10 records, and the next two strongest pairs share 4 each — signalling that related entities within the same corporate group file jointly rather than most collaboration crossing company lines.
Latest-year filings read as zero for most leaders
Several of the most active historical assignees show 0 filings in the latest tracked year, including a -100% YoY reading for one. Given the roughly 18-month publication lag, this is best read as incomplete data rather than a stop in filing.
| Assignee | Recent year | YoY |
|---|---|---|
| Samsung Electronics Co., Ltd. | 0 | — |
| Sony Interactive Entertainment LLC | 0 | — |
| Sony Advanced Visual Sensing AG | 0 | — |
| Sony Group Corporation | 0 | — |
| Magic Leap, Inc. | 0 | -100% |
| Insightness AG | 0 | — |
| Sony Europe B.V. | 0 | — |
| Harman International Industries, Inc. | 0 | — |
Where to take this analysis
The numbers above establish concentration, trend direction and technology mix. The next steps are about applying that to a specific filing or freedom-to-operate question.
Map a specific claim against the leader's portfolio
With one assignee holding 63 of 278 records, checking a draft claim against that portfolio specifically — not the field average — is the highest-value single search.
Explore assignee portfolios in EurekaTrack the under-claimed branches as they mature
Positioning and fusion classes carry noticeably lower filing density today; watching whether that changes over the next few publication cycles flags emerging competitive pressure early.
Set up class-level monitoring in EurekaCommon questions about event-based vision sensor patents
A dynamic vision sensor reports per-pixel brightness changes asynchronously as they occur, rather than reading out every pixel on a fixed frame clock. This gives much higher temporal resolution for fast motion and lower bandwidth when a scene is mostly static, since pixels that see no change stay silent. Patent claims in this dataset frequently center on contrast threshold settings that decide what counts as a reportable change, and on circuits that filter background activity noise from genuine events.
Filing in this field is concentrated: across the 54 ranked assignees, the top 5 combined account for 178 of the 278 records in scope, or 64.0% of the field, and the leading single assignee holds 63 records on its own. That leaves a long tail of smaller filers with a handful of records each. Anyone evaluating freedom to operate should check the leading assignee's portfolio specifically rather than assuming the field is evenly spread.
Filing peaked at 46 records in 2020 and eased to 23 by 2024, a -21% change from the 29 filed in 2021 — a real but moderate pullback, not a collapse. Data for 2025 and 2026 is still incomplete because publication typically lags filing by around 18 months, so those recent years will look thinner than they eventually turn out to be. Judging the field's current trajectory from the last one or two years alone would be premature.
H04N, the pictorial-communication and video-transmission class, covers 53.2% of the 278 records in scope, and G06T, image data processing and generation, covers 42.8%. Because a single filing can carry several IPC codes, these shares overlap and add to more than 100%. Classes tied to measurement and positioning, such as G01B and G01S, sit well below 15%, suggesting comparatively less claim density in sensor-fusion-for-localization applications.
US20240064424A1, filed by Sony Semiconductor Solutions, describes a noise filtering circuit that opens a timeframe when a pixel group detects a first event and then decides whether a subsequent event from the same pixel group falls inside that window before forwarding it for arbitration. That is a specific mechanism for suppressing background activity noise, not a claim over event-based sensing broadly. Entrants building their own timing-window or threshold-based noise filter would need to design around the specific arbitration-logic mechanism described, most practically by using a different criterion for correlating first and second events.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.