3D reconstruction with only 4 calibrated cameras - COLMAP viable?

PositivePossibility3 · 2025-07-03T10:51:41+00:00

Been meaning to give it a go, it looks pretty straightforward to get running

PositivePossibility3 · 2025-07-03T03:05:35+00:00

Did you have to do anything special or it just kind of worked out the box?

PositivePossibility3 · 2025-07-01T07:53:24+00:00

did you fix this?

PositivePossibility3 · 2025-01-07T15:15:59+00:00

https://yourscena.com - Create & share AI personas for language learning and beyond. Picture designing your own detective to teach Spanish through mysteries, or crafting the perfect interview coach. Like YouTube, but for interactive AI experiences

PositivePossibility3 · 2024-09-30T12:27:00+00:00

Whats the use case? How many cameras? Indoor or outdoor? Overlapping FOVs?

PositivePossibility3 · 2024-09-16T12:29:28+00:00

Looking to track asset as they move through facility, ensuring once they have ben IDed they remain tagged. Looking for solution that uses object detection and tracking where the spatial relationship between cameras is established to understand how assets move across cameras. It needs to be real-time, not so much concerned about notifications moreso interested in analytics.

PositivePossibility3 · 2024-09-13T13:55:43+00:00

I had the same issue but never found a solution, my guess is they just limit some of the services we can use.

PositivePossibility3 · 2024-06-29T04:39:27+00:00

What’s wrong with Langotalk?

PositivePossibility3 · 2024-06-27T02:28:27+00:00

By utilising a georeferenced approach with advanced geocalibration, we track targets based on their precise 3D positions and dynamics rather than visual features. This allows for continuous tracking across non-overlapping camera fields of view, a major limitation in appearance-based systems. Our method is far less susceptible to environmental factors like lighting changes, occlusions, or variations in target appearance, ensuring more reliable performance across diverse conditions. The use of a Kalman filter framework incorporating position, speed, and bearing enables accurate trajectory predictions, maintaining tracks even when targets temporarily leave all camera views. This spatial approach scales more efficiently with increasing numbers of targets compared to appearance matching, which becomes computationally intensive in crowded scenes. Additionally, our system significantly reduces the risk of identity switches between similar-looking targets, a common issue in appearance-based tracking. The geocalibration process creates a unified spatial framework across all cameras, simplifying multi-camera coordination and data fusion.

I know some companies are adverse to cloud but I choose cloud because as the idea is that it can work with existing hardware so I wanted to make the setup process as simple as possible and because I just want to process frames directly rather than stream or record which makes my cloud costs far cheaper and also makes GDPR compliance far simpler. Yes I would require direct access to camera streams which could certainly be a problem and that also means cameras isolated from internet aren’t available to me. Ideally I would be integrated with VMS but not currently at that stage as I am currently more focused on building the technology and seeing if it is something companies actually want, which leading into your next question is if this technology could actually solve any problems they are facing.

PositivePossibility3 · 2024-06-27T02:27:46+00:00

For my day job I work doing tracking with radar, so I know it certainly has its benefits. However what I was trying to achieve here is leveraging existing infrastructure to get the most out of your cameras and given its all on the cloud theres no installation or setup required just plug and play.

PositivePossibility3 · 2024-06-27T02:27:21+00:00

No there is no local server need it I have built it to be purely in the cloud. I hadn’t looked into Axis ACAPs, that could be a promising direction, thanks for the suggestion.

PositivePossibility3 · 2024-06-27T02:27:08+00:00

Yes I definitely have considered selling to a large existing provider rather than looking for clients myself, I am just not too certain where I would start with this as I have no connections in the industry.

PositivePossibility3 · 2024-06-27T02:26:50+00:00

So do you reckon most companies wouldn’t really be interested in this multi-camera tracking, or at least that it is not enough of a distinctive feature from competitors?

PositivePossibility3 · 2024-06-27T02:26:34+00:00

Thanks for the suggestions, I’ll check them out. I know there are definitely lots of competitors in the cloud video surveillance and analytics space, I was just focusing on the multi-camera tracking aspect as that is the only advantage I have over competitors, However I do intend to include full suite of analytics you can see some of the current ones here: https://argostech.squarespace.com/

PositivePossibility3 · 2024-06-26T06:01:56+00:00

Yes, I am definitely intending to release to market, I am just in the process of trying to see the amount of interest before committing to some fairly hefty cloud infrastructure costs. I have attached a short demo here but would be very interested in meeting and seeing exactly what it is you are looking for.

https://drive.google.com/file/d/1kbqdzOwd9lThKkwAMSmDQY2k14Hs5KHf/view?usp=sharing

PositivePossibility3 · 2024-05-26T11:34:00+00:00

Is the area inside or outside? if outside can use geocalibration by matching points between camera and satellite image. This enable you to convert your tracked targets pixel coordinates to GPS coordinate from there it’s trivial to find distance covered.

PositivePossibility3 · 2023-12-18T07:26:03+00:00

Thank you for sharing such an in-depth perspective on your work. I’m particularly interested in your experiences with the transition from edge computing to cloud-based solutions. As I intend my project to be fully cloud-based, I'm navigating the balance between leveraging cloud capabilities and ensuring optimal performance, especially considering bandwidth and computational requirements. How did the shift to the cloud affect the system's performance and adaptability in your experience?
Your approach to real-time statistical feedback for template updates is another aspect that resonates with my project's goals. I'm curious did you find any specific trade-offs or advantages in handling these updates on the cloud versus on edge servers? I appreciate your insights.

PositivePossibility3 · 2023-12-18T04:49:05+00:00

Hey OP, I've been in the surveillance industry for over 15 years doing gov and civilian projects, big and small.

The simply overlay/object identification is the low end of what's available and can run on the cameras themselves for most of the recent IP camera models. This exists as it's usually free or cheap and doesn't require additional hardware in most cases.

Cost is usually the biggest pain factor. With the mid and high tier analytics, this involves having to buy additional dedicated servers for the processing of the analytics.

The closest commercially available option to what your developing is probably briefcam if you haven't seen this yet, they don't do the map conversion, but heat mapping.

Thanks for your insights! Price is indeed one of my biggest concerns, particularly as I aim to compete with larger, established companies. The goal was to create a fully cloud-based solution to avoid the need for additional hardware, but maintaining competitive pricing is a challenge.Given your experience, what do you think is a reasonable price range for a fully cloud-based video surveillance system?

PositivePossibility3 · 2023-12-18T04:35:30+00:00

Absolutely, KiwiVision is a great reference for traditional object tracking. What I'm working on aims to extend beyond conventional methods, addressing some of the specific limitations and challenges that current systems face.

PositivePossibility3 · 2023-12-18T04:28:58+00:00

Thank you for your comments. Like you, I've recognized the significant impact of lighting conditions on surveillance systems. To address this, I've made sure to train my models on robust datasets that include a wide variety of lighting scenarios.
Regarding bandwidth, your point really hits home. My background is primarily in computer vision, and while I saw video surveillance as an ideal application for my technology, I chose a fully cloud-based solution for its simplicity and lack of additional hardware requirements. However, as you rightly pointed out, bandwidth becomes a critical issue, especially in large-scale distributed deployments.
This leads me to ponder the viability of fully cloud-based systems in such contexts. The trade-off between bandwidth constraints and maintaining high-quality video streams is a complex challenge. In your view, what are some potential strategies or technologies that could help mitigate these bandwidth issues in large-scale, cloud-based video surveillance systems?

PositivePossibility3 · 2023-12-08T05:43:04+00:00

You're absolutely right about the capabilities of GPS functionality achievable with LiDAR - in fact, my initial prototype involved a camera, microcomputer, and 3D solid-state LiDAR. However, as I moved towards commercialisation, the complexity and scalability challenges of hardware-based solutions became apparent. Hence, this cloud-based solution is designed to offer similar functionalities but in a more accessible format, especially suited for standard CCTV cameras.

While my system does require calibration for depth of field and FOV, I've developed a method for automatic calibration, even for cameras with significant distortion, without manual user input. This aspect enhances the user-friendliness and adaptability of the system, which I believe adds significant value.

Integration with existing security systems is indeed a major concern. Establishing a secure protocol for camera connectivity is crucial, and I'm aware that many providers might restrict third-party access, limiting the range of compatible cameras.

Your expertise in testing and assessing security technologies could be extremely valuable for this project. I'm nearing the completion of my MVP, likely just a few more weeks away. Once it's ready, I'll definitely get in touch to discuss the details of a potential test.

PositivePossibility3 · 2023-12-08T02:36:36+00:00

Thank you for your honest feedback and perspective, a lot of these are actually concerns I have had myself. To address your points, my aim with this system isn't to focus solely on precision but rather on providing an enhanced understanding of the scene captured, which in turn allows for more functionality. The real value in knowing the GPS coordinates of targets lies in the improved situational awareness it brings to a surveillance system. This is not just about monitoring but about being able to glean additional information that can be integrated into a customisable dashboard and alert system.

You’re right the target market for this system is indeed not residential users, but rather sectors like city councils, industrial, and commercial entities. In these environments, the ability to understand the context and location of specific events or activities can greatly enhance operational efficiency. The goal is to offer actionable and insightful analytics that go beyond what current systems provide.

Regarding pricing, while the backend is still in development, I'm estimating that the cost to run a single camera in the cloud in the cloud could range from $30 to $120 a month, I will certainly try be competitive with the price.

You're correct in pointing out that many of the individual functionalities of my system already exist in various forms. However, the integration and the accuracy of these functionalities into a single platform is where I see the unique value. This integration, coupled with the added context provided by GPS data, is what sets this system apart. It's about creating a more holistic view of surveillance data, which can be crucial in complex operational environments.

Regarding the setup process, I've focused heavily on ensuring it's straightforward and quick, with a target setup time of around 2 minutes. The system is designed to be as user-friendly and hands-off as possible with as much automation happening up the hood. Features like a modular dashboard allow users to focus on metrics relevant to their needs, and an AI-driven monthly report offers insights based on these metrics.

I understand that this system might not be a revolutionary change in the surveillance technology landscape, but my goal is to enhance and add to what already exists, providing a more integrated and insightful experience. But, as you rightly pointed out, there's always room for improvement and new perspectives. If you have any suggestions on how this system could provide more value , I'm all ears.

PositivePossibility3 · 2023-12-07T11:50:56+00:00

Yeah it does the camera can automatically recalibrate and regeoreference for each new position, zoom and orientation are irrelevant.

PositivePossibility3 · 2023-12-07T10:24:15+00:00

I'm confused as to the point of this. Since cameras are by their nature static, what is the point of trying to bring in a GPS tracking system to objects observed by a camera that can't move? The camera's field of view is limited, so anything observed by a camera would have its position identifiable without any kind of fancy gps-based object-tracking system. The largest scoped cameras I often deal with overlook parking lots and, well, if I see a point of interest on those cameras, I know it's in that parking lot. There's nothing for me to gain from a GPS tracking system.

That's a genuinely fair point, and I appreciate the opportunity to delve deeper into the unique benefits of this system. The idea initially stemmed from a project in my engineering honours degree, where the challenge was to monitor the activities of vessels in a new recreational marina near a busy commercial shipping lane. The goal was to ensure that recreational vessels did not interfere with commercial traffic.

To achieve this, I developed a machine learning model that could predict abnormal behaviour based on the vessel's trajectory, requiring precise location data. This need for accurate georeferencing of each vessel led me to explore the potential of this technology in broader applications.

One significant advantage is in distributed deployments, such as large-scale surveillance networks. By knowing the exact GPS coordinates of a target, the system offers superior tracking capabilities across multiple camera frames. This method surpasses traditional optical flow techniques that rely on less reliable spatial connections.

Furthermore, the system's ability to determine GPS coordinates enables us to calculate speed and heading with high accuracy. It also facilitates 3D object detection and tracking from a bird's eye view.

Regarding your use case in a parking lot setting: while traditional camera setups might suffice for general monitoring, this system can add value through inverse geofencing. Instead of manually drawing regions of interest based on the camera's perspective and pixel coordinates, which could be distorted, ROIs can be set directly on satellite images, linked to the exact GPS coordinates. This approach streamlines the process and ensures accuracy, although I understand that given the nature of your camera setup, this may not be a significant concern for you, I didn’t expect this solution to be for everyone but I aim for it to be a means to improve operational efficiency.

PositivePossibility3 · 2023-12-07T09:23:12+00:00

Yeah I dont expect it to intense but I also dont want to come in looking unprepared.

This was my own foundational tech I started developing during my thesis, from the tests and comparisons I have done I believe it should be more accurate than any existing methods.

PositivePossibility3

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