I'm a bit confused about your product lines technology integration - "Video" and "Sentry". The video app works great, but the Sentry technology is fantastic in detecting stuff. Yet the features on one are not available on the other. Why not integrate them into a single product??
Here's a basic need for a security system:
- Real time detection of the faces of family members, friends, employees, etc., known people that the security system can safely ignore.
- Any other person detected will send an alert.
- Same with cars. The system should alert me of unknown license plates, type of car, etc. other than my own or belonging to known friends and family members. Or just log detected license plate and car data to a database.
Why not make a cloud subscription available that connects the "Video" product to your "Sentry" detection system and make it more useful?
Thanks
Video Integration with Sentry
Moderator: Staff
4 posts
• Page 1 of 1
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sumguy - Posts: 5
- Joined: Mon Nov 07, 2016 3:03 pm
Re: Video Integration with Sentry
Agreed! I would also like these features integrated into Video. I am a home user and have an advanced home automation system. I have been looking for LPR and Facial Recognition features for a while now and there is no video software out there that offers a complete solution to the home user.
SH has already developed the technology, why not offer it across both products?!?!
SH has already developed the technology, why not offer it across both products?!?!
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Stephen Neish, CEO - Posts: 23
- Joined: Mon Nov 21, 2016 6:02 pm
Re: Video Integration with Sentry
Hello Pando,
For now we have three product lines: Cloud for developers, Sentry for OEMs and Video for consumers. You are right that Sentry and Cloud have more advanced computer vision offerings than Sighthound Video. We are looking at adding to the functional capabilities of Sighthound Video, however there are various factors at play:
- Some of the features are computationally expensive, and so there is a limit on what can run locally
- Our users are very concerned about privacy. At the moment none of your home video goes to our Cloud servers, and many users want it to remain that way
- Our users are worldwide, and some have limitations on sending content to US-based servers
- In some of your examples the video stream would need to go to the cloud to get an answer, which could impose upload bandwidth issues
- We have not yet finished adding the most-requested features to SV
Having said that, these issues are not insurmountable. We could introduce cloud-assisted processing as an option so that those who never want video to leave their computer have control; we could use some of the CPU gains won in v4.0 for more complex CV on device; and we are rapidly making progress through the most-requested features.
So, more to come on this subject, but implementation issues aside, you make a valid point. Sighthound has a suite of the most accurate computer vision capabilities in the world, and one of the most popular home surveillance products in the world. The two would be better together.
For now we have three product lines: Cloud for developers, Sentry for OEMs and Video for consumers. You are right that Sentry and Cloud have more advanced computer vision offerings than Sighthound Video. We are looking at adding to the functional capabilities of Sighthound Video, however there are various factors at play:
- Some of the features are computationally expensive, and so there is a limit on what can run locally
- Our users are very concerned about privacy. At the moment none of your home video goes to our Cloud servers, and many users want it to remain that way
- Our users are worldwide, and some have limitations on sending content to US-based servers
- In some of your examples the video stream would need to go to the cloud to get an answer, which could impose upload bandwidth issues
- We have not yet finished adding the most-requested features to SV
Having said that, these issues are not insurmountable. We could introduce cloud-assisted processing as an option so that those who never want video to leave their computer have control; we could use some of the CPU gains won in v4.0 for more complex CV on device; and we are rapidly making progress through the most-requested features.
So, more to come on this subject, but implementation issues aside, you make a valid point. Sighthound has a suite of the most accurate computer vision capabilities in the world, and one of the most popular home surveillance products in the world. The two would be better together.
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Pando - Posts: 6
- Joined: Thu Mar 17, 2016 11:37 am
Re: Video Integration with Sentry
Thank you, Stephen, for your insights. I truly believe that with better integration of your core technology, your products (and your company) would be much more successful.
If I may respond to a few of the points you made:
Your "video" product already detects people. Have it send a face of the person (or a hashed version) to the cloud, and return an anonymous ID to the "video" product where it is checked against a local database of IDs (or hashes). There is no need to stream the entire video to the cloud, nor is there a need to run computationally expensive processes (like face recognition) locally. Have a business plan - leverage the cloud when needed, and finance the cloud resources with a monthly subscription from your customers who need this service.
Valid point, but give users the control what gets sent to the cloud. Also, as already stated above, there is no need to send the entire video to the cloud.
Yes, but why handicap US-based users? I'm sure it's possible to make your services available based on regional limitations.
But why limit your technology for users who do have the capability? There are plenty of users/businesses with more upload bandwidth available than what they ever use or know what to do with. Also, again, the entire video stream should not need to be streamed to the cloud.
Here is an idea how this would work:
Your detection of celebrities is already pretty astounding. Using the same technology you already have, create software that does the same thing locally, but using cloud resources for real-time detection.
For example: Have the user store a couple of pictures of family members or employees in the "video" software and let the software compute a hash for each face (as it only needs to be done once, it doesn't have to be real time, or have the cloud do that). Store the hashes in the cloud as part of a subscription. Then, as the "video" software locally detects a person, it immediately sends the face portion to the cloud as a snapshot. The cloud runs the analysis quickly, returns the hash to local user where it's then compared against known user database, and take whatever action is needed (send alert if there is no match, etc.). The cloud can immediately delete actual the snapshot, and since only hashes are stored in the cloud and returned, there should be no privacy issues.
If I may respond to a few of the points you made:
- Some of the features are computationally expensive, and so there is a limit on what can run locally
Your "video" product already detects people. Have it send a face of the person (or a hashed version) to the cloud, and return an anonymous ID to the "video" product where it is checked against a local database of IDs (or hashes). There is no need to stream the entire video to the cloud, nor is there a need to run computationally expensive processes (like face recognition) locally. Have a business plan - leverage the cloud when needed, and finance the cloud resources with a monthly subscription from your customers who need this service.
- Our users are very concerned about privacy. At the moment none of your home video goes to our Cloud servers, and many users want it to remain that way
Valid point, but give users the control what gets sent to the cloud. Also, as already stated above, there is no need to send the entire video to the cloud.
- Our users are worldwide, and some have limitations on sending content to US-based servers
Yes, but why handicap US-based users? I'm sure it's possible to make your services available based on regional limitations.
- In some of your examples the video stream would need to go to the cloud to get an answer, which could impose upload bandwidth issues
But why limit your technology for users who do have the capability? There are plenty of users/businesses with more upload bandwidth available than what they ever use or know what to do with. Also, again, the entire video stream should not need to be streamed to the cloud.
Here is an idea how this would work:
Your detection of celebrities is already pretty astounding. Using the same technology you already have, create software that does the same thing locally, but using cloud resources for real-time detection.
For example: Have the user store a couple of pictures of family members or employees in the "video" software and let the software compute a hash for each face (as it only needs to be done once, it doesn't have to be real time, or have the cloud do that). Store the hashes in the cloud as part of a subscription. Then, as the "video" software locally detects a person, it immediately sends the face portion to the cloud as a snapshot. The cloud runs the analysis quickly, returns the hash to local user where it's then compared against known user database, and take whatever action is needed (send alert if there is no match, etc.). The cloud can immediately delete actual the snapshot, and since only hashes are stored in the cloud and returned, there should be no privacy issues.