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VicoVation Opia1 Dash Camera

VicoVation Opia1 Dash Camera

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Product Description
Offering excellent video quality and a slew of modes, the Opia1 from VicoVation is a solid bet for any driver. Thanks to the Sony STARVIS sensor and Novatek chipset, the dash cam provides full HD footage at 60 frames per second Read More

1080p Footage, Heat-Resistant Build

Offering excellent video quality and a slew of modes, the Opia1 from VicoVation is a solid bet for any driver. Thanks to the Sony STARVIS sensor and Novatek chipset, the dash cam provides full HD footage at 60 frames per second. The wide-angle lens captures up to a 145-degree angle to get everything in the scene. With this model, you can also play your footage back over the OPIAViewer app through your smartphone. Aside from video quality, the build quality is top notch as well. A supercapacitor allows the dash cam to record at temperatures up to nearly 160 degrees, and the adhesive mount is nice and strong to keep the device from rattling around. As far as modes, the Opia1 has parking mode, a built-in G-sensor, loop recording, and time lapse mode, too.

Note: At checkout, you can add a hardwiring kit for (+ $35).

VicoVation Opia1 Dash Camera
VicoVation Opia1 Dash Camera
VicoVation Opia1 Dash Camera

Specs

  • Resolution: Full HD 1080p at 60fps
  • Sony STARVIS sensor
  • Parking mode (CCTV mode)
  • G-sensor: Built-in
  • Wide angle view: 145°
  • Operating temperature: -10 ~ 70°C (14° ~ 158°F)
  • Loop recording
  • Maximum SD card: 128GB
  • LCD
  • 802.11n Wi-Fi
  • Smart parking mode
  • Time lapse mode
  • 7G glass lens
  • Microphone: Built-in
  • Speaker: Built-in
  • File format: .MP4
  • Country of origin: Taiwan

Included

  • Power cord
  • 32GB memory card

Optional Hardwiring Kit

  • Output current: 1A (max 2A)
  • Standby current: <0.1 mA
  • 12V cut off: 11.4 - 12.6 V (0.2V increments)
  • 24V cut off: 23.2 - 24.6 V (0.2V increments)
  • Low voltage protection
  • Parking mode bypass
  • Timer cutoff
  • Temperature cutoff
  • Country of origin: South Korea

Shipping

Estimated ship date is Feb 28, 2019 PT.

Payment will be collected at checkout. After this product run ends, orders will be submitted to the vendor up front, making all orders final.

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Recent Activity
I've played with h264 and h265 and there are some interesting results on the amount of storage that can be saved, and perhaps that helps. As the storage sizes increase with microSD, that gives one hope for the size that can be stored which results in larger video assets. Obviously, one could simply make a custom storage for such, but depending on one's travel times and implementation, I don't know how much of a necessity that is. The other factor is noting the more sophistication one has with their encoder, the more power consumption and computational power needed to get those results. Again, probably not an issue here, but I'm just making sure that is recognized. To sort that out, I guess I would have to ask about the implementation. Do these dash records run all the time regardless and at the end you simply take your clips off if you choose? Or do they activate based on an event such as a button press, etc to tell it to start recording? If it is the latter, then I would think it would be reasonable to use 4K. Regarding the comment about HD not having enough resolution to pick out a license plate and faces, I would think that it would, but I think the quality of lens and sensors would be an issue here. Don't get me wrong; I recognize that the more pixels one has for producing an image, the better definition one has. I guess I base this on the quality of cameras that have been used in the past for this work. Typically, many of these solutions have a better analyzer to know how to recognize these plates and such. Granted, it sounds like you are discussing your ability to see the license, but I note that people have approached this issue on their own: https://medium.freecodecamp.org/how-i-replicated-an-86-million-project-in-57-lines-of-code-277031330ee9 If you could modify the recognition part of code, read the coordinates of the image where the plate is, then have a camera system (like what one finds in cell phones for example) and have it zoom on that location for the read, that would be a decent method for handling it, but I'm deviating from the original purpose as you are stating you simply want the clips to be recognizable for a human and not bring AI in the mix. That being the case, I really think you would need a much better camera system to get the results you want, so I think you would be justified in passing over this system regardless (unless you can get a try before you buy).
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