Bosch Person / Car / Bike / Truck Analytics Tested

By Ethan Ace, Published on Jun 05, 2015

Automatically identify what objects are persons vs cars vs bikes vs trucks. That is the new feature and claim from Bosch in their newest IVA analytics (6.10 version). 

We first tested Bosch IVA here. With this new feature, we wanted to see how accurately this worked.

This video shows the basic setup process we used before testing:

We tested these analytics on multiple cameras in a busy outdoor scene, to answer these questions: 

  • Are cars, trucks, people, and bikes reliably detected and classified?
  • What objects are missed most often?
  • How do busy scenes impact performance?
  • Are VMSes able to receive these events distinctly?
  • *****'* *** ****** ************** was **** ******** **** cars *** ******. ** low ******** ******, ********* and ******* ************** ** these ******* ****** * ~190' field ** **** *** ********, missing *** *******.

    ********* ** ****** *** less ********, **** ******** cars ******* ******** ********** as * *****, *** some ******* ****** ********** as ****.

    ******** **** ********** ***** reliably, **** ****** ******* **** strollers **  *** **** cars ******** ** *****. Actual ******** **** ************ missed ** ********** ** another **** ** ******.

    *** ******** *********** *** object **************, ********* ***** to ******* ******** **********/******** lines, ** **** ** one ** **** ****** for ****** *********. *********** was ****, ** ***** measurements *** *****, *** roughly ******** ** *** size/distance ***********.

    ***** *** ****** ********** with ******* ******** ****** and ********* ********, **** distinct ***** ******** ********** (e.g., ****** ********* **. vehicle *********, ***.).

    ***************/******

    **** ***** ***** ***** object ************** *********, *****'* IVA ********* **** * step ****** ** ******** to ****** *** ******** providers **** ********/******* *** AgentVI, ***** **** ******* these ************ *** **** time.

    *******, ***** ****** ** careful ** ***********, *** limit ***** ***** ********* are ********, **** **** activity ****** ********** ******* objects ** ***** *** be *************. ************, ** recommend ******** ************ ** people **. ******** (**** cars *** ******), ** proper ********* ** ******** performed *****.

    Firmware ************

    ***** ************ ** *** are ********* ******** ** firmware *.**, ********* *** most ******* ** ******* in *** ***** ****. Firmware ** ********* *** download **** *** ***** Security *******.

    VMS ***********

    *** ******* ****** ******** events ** ******* ******** Center *** **** *** rule ******* ** *** camera. **** ** ***** in *** ***** ****, here, **** ****, ******, and ******* "****** *** object" ***** ***** **********.

     

    ********* ******** ******** ** to ** ******** ***** analytics ****** **** ***** IVA *******, ****** **** names *** *** ****** from *** ****** *** must ** ********** **********.

    ******** ******* ****** *** Exacq *** *** ******* these ******** ******, **** basic ****** *********.

    Calibration *******

    *********** ******** ***** ** mark ***** *********, *******, and/or ****** ** *** camera's ***** ** ****. We ********* *********** ***** Google **** ************ *** angle ********* *** ***** it ** ** ****** accurate, ****** * *** feet ** ****** ************.

    **** ******* ** ******** in *** ***** *****:

    Detection ***********

    **** ****** ******** ** the *****, ****, ******, and ****** *** ********** correctly >**% ** *** time. *** *******, ****** flags *** **** *** people *** ** **** correctly ******** ** *** respective ******* ** **** image:

    ********* *** ******** *** people, **** **** ******** objects ** *** *****.

    **** *** ****** **** correctly ********** ** *** majority ** *****, ****** there *** **** ******* with ******, ********* ** size (*****):

    *******, **** * **** (bicicyle ** *********) *** present, ** *** ********* classified ** *** *****, such ** *** *** seen ****:

    Misclassification ******

    *******, ****************** **** ****** for *****, *** ** a ****** ******, ******.

    ******* ******* ** "******"

    **** ********, ****************** **** caused ** ******** ******* grouped ******** **** ***** was **** ******** ** the *****, ********* ** a ****** ****** ****** to *** ******. **** was **** ***** *** to * ***** ** cars ********* ** * truck, **** ****:

    ** *** ************* *******, the *********** ******* **** and ****** ** ****** most *****. *********, ***** want ** **** ******* a ******* ** *******, regardless ** *** ****. However, ** **** **** specialized ************ (*.*., ******* or ******* ***** ****** are **********, ****-**** *********, etc.), ********* ** *** distinct ******* ** *********.

    ***** ******* ********* ** Bikes

    ***** **** *** **** common *********** ****** ****, with *********** ***** ***** object **** ********* ** a **** ** *** camera ** *** ***** or *******. 

    *** *******, * ***** subject **** * ********:

    ** ******* * ******:

    **** ** **** ** these *****, *** ****** is *******, ** * similar ******* ** ******* riding * ****, ****** the ****** *** *** misclassification.

    *******, ** *** ***** case, *********, * *** was ********** ** * bicycle ** ****:

     

    Cameras **** 

    *** ******* **** **** for **** ****:

    • ***** ***-*****: *.**.****
    • ***** ***-****: *.**.****

    ******* ******** ****** *.* SR9 *** **** *** recording.

Comments (14)

I'm curious how it would work with a different FOV. Two things I notice:

1) The camera seems relatively low, it looks like maybe 8-9' high. I would expect improved results from a higher vantage point with a little more downward tilt of the camera

2) The FOV seems exceptionally wide and you appear to be getting barrel distortion from the lens. Looks like a ~3mm lens. I'd suggest trying something no less than 4mm to get a flatter image and to keep the overall horizon line and geometry more squared up.

What was the logic in using this FOV? Was it more or less random in the sense you picked a "typical" scene, or did it conform to some recommendations from Bosch?

Are the analytics included with the camera purchase similar to the way Samsung bundles them in with the WiseNetIII. Overall they appear to work fairly well. It will be interesting to see how they perform over a longer period of time. I have had issues with "in camera" analytics where they just stop sending alerts and the camera needs to be rebooted.

They're included on all 7000/8000 series cameras at no charge (5MP starlight, 1080p HDR, 4K, etc.), but not on the 5000 series.

I think that Bosch is trying to do too much.

Avigilon approach of people/cars is much more reliable as I don't see any tech today that can really detect a the difference between a person and a bicycle.

Its better to do less in a good way than to do more poorly.

Finally, when a bike (bicicyle or motorbike) was present, it was correctly classified in all cases...

However, misclassifications were common for bikes...

Meaning other types were commonly misclassified as bikes, since no bikes were actually misclassified?

Correct.

Ethan could you post some video clips from the intersection shot showing objects being detected? Also could you show images/video of the calibration setup for the intersection?

Just following up with the request for some video clips from the street shots.

I would really like to know detection ranges in day and night scenarios, with the lens length or angle used. That to me are the most important numbers along with reliability. Getting an idea of reliable ranges gives you an idea of how many cameras are needed for coverage.

In this test we were trying to get an idea of how well classification worked, not intending this to be a redo of their IVA detection performance. We tested that here (and in the rain). That being said, in this scene, I'd say detection of humans was reliable out to about 150' using the Bosch 5MP, or about a 285' HFOV, something like this:

I know I asked already asked but could you please post some video so we can see the detection range.

The issue with video clips here is that Bosch doesn't embed bounding boxes in the video (like Avigilon no longer does), and to my knowledge, no one has integrated the bounding boxes via metadata other than their own VMS, which we don't use. So we can see them live using Configuration Manager, but Genetec (which fully integrates the separate rules, sans bounding boxes) doesn't display the box.

So I can show you clips and you can see what is in the scene, but it's not going to show you bounding boxes. It's not going to show you events as they happen, either. Video associated with each event can be exported, but multiple events can't be exported with one stretch of video.

I will look through what we have saved as far as config/screen captures of Configuration Manager, as that's the only thing that'll show bounding boxes and path.

The cameras tested here don't support The Bosch CPP6 platform on which this IVA version is supported, therefore tests are i"not really relevant. Re-test on the Starlight 8000 and would be interesting to see results.

1. We used a Starlight 8000, the NBN-80052, as we mentioned in the report. The images in the report are taken from that camera.

2. As per Bosch's documentation IVA 6.10 is supported on more than CPP6.

IP cameras from Bosch are grouped by their common
product platform (CPP) generation. IVA 6.10 is
available on CPP4 and CPP6 based IP cameras

The NBN-932 (now numbered NBN-71027) is CPP4, and supported.

Read this IPVM report for free.

This article is part of IPVM's 6,602 reports, 890 tests and is only available to members. To get a one-time preview of our work, enter your work email to access the full article.

Already a member? Login here | Join now

Related Reports

Uniview Deep Learning Camera Tested on Jul 14, 2020
Uniview's intrusion analytics have performed poorly in our shootouts. Now,...
Vivotek LPR Camera Tested on Apr 15, 2020
Vivotek has historically sold license plate capture cameras but not LPR. Now,...
Tiandy Super Starlight Cameras Tested on Apr 30, 2020
Tiandy is taking aim at China competitors Dahua and Hikvision, with a new...
Hanwha AI Analytics Camera Tested on Aug 11, 2020
Hanwha has released their Wisenet P AI camera, adding person and vehicle...
YOLOv5 Released Amidst Controversy on Jul 27, 2020
YOLO has gained significant attention within video surveillance for its...
Hanwha AI Object Detection Tested on Sep 28, 2020
Hanwha has added detection and classification of people, cars, clothing...
Mobotix Thermal Detection Camera Tested on Jun 09, 2020
For years Mobotix has struggled but now sales are surging driven by Mobotix's...
Verkada 2020 Cameras Image Quality Test on Oct 06, 2020
Verkada's first-generation cameras suffered from numerous video quality...
Verkada Video Analytics Tested 2020 on Oct 08, 2020
In 2019, Verkada released people and face analytics but our testing then...
Avigilon UMD / UAD Tested on Oct 14, 2020
Avigilon's Unusual Activity Detection and Unusual Motion Detection claim to...
Security And Safety Things (S&ST) Tested on Oct 22, 2020
S&ST, a Bosch spinout, is spending tens of millions of dollars aiming to...
YCombinator AI Startup Visual One Tested on Apr 02, 2020
Startup Visual One, backed by Silicon Valley's powerful Y Combinator, aims to...
Video Analytics 101 on Mar 16, 2020
This guide teaches the fundamentals of video surveillance...
Cisco Meraki Unlocks IP Cameras With RTSP Tested on Jul 06, 2020
Meraki opened up its cameras to 3rd party NVRs/VMSes by offering RTSP...
Exacq "Facial Matching" Facial Recognition Tested on Sep 03, 2020
Exacq is claiming "Accurate Recall of Every Noteworthy Person of Interest"...

Recent Reports

Recruiters Online Show LIVE Today! on Oct 29, 2020
IPVM's 7th online show resumes today with 12 recruiters presenting themselves...
Hikvision AcuSense G2 Camera Test on Oct 29, 2020
Hikvision has released their next generation of AcuSense analytic cameras...
Biggest Problems Selling Access Control 2020 on Oct 29, 2020
Access control can cause integrators big headaches. What practical issues do...
Taiwan Geovision AI Analytics and NDAA Examined on Oct 29, 2020
Taiwan manufacturer Geovision's revenue has been falling for years. However,...
Bedside Cough and Sneeze Detector (Sound Intelligence and CLB) on Oct 28, 2020
Coronavirus has increased interest in detecting symptoms such as fever and...
Fever Tablet Thermal Sensors Examined (Melexis) on Oct 28, 2020
Fever tablet suppliers heavily rely on the accuracy and specs of...
Verkada Fires 3 on Oct 28, 2020
Verkada has fired three employees over an incident where female colleagues...
Eagle Eye Networks Raises $40 Million on Oct 27, 2020
Eagle Eye has raised $40 million aiming to "reinvent video...
Hikvision Q3 2020 Global Revenue Rises, US Revenue Falls on Oct 27, 2020
While Hikvision's global revenue rises driven by domestic recovery, its US...
VICE Investigates Verkada's Harassing "RawVerkadawgz" on Oct 26, 2020
This month, IPVM investigated Verkada's sexism, discrimination, and cultural...
Six Flags' FDA Violating Outdoor Dahua Fever Cameras on Oct 26, 2020
As Six Flags scrambled to reopen parks amid plummeting revenues caused by the...
ISC Brasil Digital Experience 2020 Report on Oct 23, 2020
ISC Brasil 2020 rebranded itself to ISC Digital Experience and, like its...
Top Video Surveillance Service Call Problems 2020 on Oct 23, 2020
3 primary and 4 secondary issues stood out as causing the most problems when...
GDPR Impact On Temperature / Fever Screening Explained on Oct 22, 2020
What impact does GDPR have on temperature screening? Do you risk a GDPR fine...
Security And Safety Things (S&ST) Tested on Oct 22, 2020
S&ST, a Bosch spinout, is spending tens of millions of dollars aiming to...