[MORPHMET] Re: Small object (insectivorous bat) photogrammetry

2016-12-14 Thread Daniel Jager
Browne, I. D. PRECISION, ACCURACY, AND REPRODUCIBILITY OF RESEARCH-QUALITY 
PHOTOGRAMMETRIC MODELS OF VERTEBRATE MICROFOSSILS IN THE 0.5–2 MM SIZE 
RANGE 
 
Santella, M., Milner, A. R. PHOTOGRAMMETRY OF MICROFOSSIL VERTEBRATE TEETH 
FROM THE LOWER JURASSIC KAYENTA FORMATION OF SOUTHWESTERN UTAH 


These were talks at the 2016 Society of Vertebrate Paleontology, but they 
should provide a good place to start.

On Wednesday, December 14, 2016 at 10:29:02 AM UTC-7, Giada Giacomini wrote:
>
> Hi all, 
>
> I am quite new to photogrammetry and geometric morphometric worlds and I 
> got a bit stocked. 
> I am trying to build 3D models of insectivorous bat skulls employing 
> photogrammetry (more details at the end) and Agisoft Photoscan software. 
> The methodology works quite well with bigger specimens (19 mm x 12 mm x 7 
> mm). 
> But with a smaller ones (e.g. 13 x 8 x 5 mm) the software has different 
> problems in the 3D reconstruction: usually it is not able to reconstruct 
> the dense cloud (doing “inside out” or providing a long scratch of points) 
> or, if the first step had worked successfully, it isn’t able to align the 3 
> chunks together. 
>
> The pictures are in focus and the specimens in the picture results big 
> enough I would say. 
> We are trying with other software different from Agisoft but the 
> reconstruction is still difficult. 
>
> Anyone of you have already tried to perform photogrammetry on such small 
> objects? 
> Do you have any suggestions or comments? 
>
> Many thanks 
>
> Giada 
>
> Photogrammetry equipment and camera settings: 
> Camera: NIKON D5300 (24 megapixel) 
> Lens: NIKON macro 60 mm, f2.8 
> Settings: 
> 4-5 cm from the specimen 
> 100 ISO 
> f/32 
> 0.5 sec exposure time 
> No flash. 3 white lights 
> Focus: automatic focus on a manual selected square 
>

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Re: [MORPHMET] Small object (insectivorous bat) photogrammetry

2016-12-14 Thread David Katz
Hi Giada,

The object may simply be too small. However...

1. My recollection is that you need to keep your f-stop much lower, maybe
f-11 maximum. Look into it. It's possible this has changed with recent
software updates.

2. I assume each chunk is a rotation around the skull. Try shooting more
than 3 rotations. For crania, I prefer 5.

3. How many photos per rotation are you using? For small primate crania, I
have used as many as 35.

4. Sometimes dirtier skulls are better than clean ones. If the bones are
bleached white, it will interfere with the ability of the program to
identify specific points.

5. Sometimes a few photographs mess up the whole alignment. If you align
each rotation individually, and your photographs are sequentially numbered,
you may be able to pick out these photographs and remove them from the
dataset.

Good luck.

David

On Tue, Dec 13, 2016 at 6:02 AM, Giada Giacomini <
giada.giacomin...@gmail.com> wrote:

> Hi all,
>
> I am quite new to photogrammetry and geometric morphometric worlds and I
> got a bit stocked.
> I am trying to build 3D models of insectivorous bat skulls employing
> photogrammetry (more details at the end) and Agisoft Photoscan software.
> The methodology works quite well with bigger specimens (19 mm x 12 mm x 7
> mm).
> But with a smaller ones (e.g. 13 x 8 x 5 mm) the software has different
> problems in the 3D reconstruction: usually it is not able to reconstruct
> the dense cloud (doing “inside out” or providing a long scratch of points)
> or, if the first step had worked successfully, it isn’t able to align the 3
> chunks together.
>
> The pictures are in focus and the specimens in the picture results big
> enough I would say.
> We are trying with other software different from Agisoft but the
> reconstruction is still difficult.
>
> Anyone of you have already tried to perform photogrammetry on such small
> objects?
> Do you have any suggestions or comments?
>
> Many thanks
>
> Giada
>
> Photogrammetry equipment and camera settings:
> Camera: NIKON D5300 (24 megapixel)
> Lens: NIKON macro 60 mm, f2.8
> Settings:
> 4-5 cm from the specimen
> 100 ISO
> f/32
> 0.5 sec exposure time
> No flash. 3 white lights
> Focus: automatic focus on a manual selected square
>
> --
> MORPHMET may be accessed via its webpage at http://www.morphometrics.org
> ---
> You received this message because you are subscribed to the Google Groups
> "MORPHMET" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to morphmet+unsubscr...@morphometrics.org.
>



-- 
David C. Katz, Ph.D.
Evolutionary Anthropology
University of California, Davis
Young Hall 204
ResearchGate profile 
Personal webpage 

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[MORPHMET] Problem with 3DPLSAngle (IMP Series)

2016-12-14 Thread stefan_curth
Hello! I'd like to compute PLS vector angles in 3DPLSAngle of the IMP series in 
order to compare two groups of specimens with regard to their morphological 
integration pattern. When I import the data of a test sample and click on "Do 
SVD", I get some angles in the output window. However, when I click on 
"Bootstrap SVD Angle" to check the range of angles within the two groups under 
comparison, nothing happens.  Also other buttons and menus seem not to react 
when clicking on them. The different file input fields say "no file loaded" 
although I can see data points in the graph to the left. 
- What am I doing wrong? Can anybody help?

Further info: I imported the test sample in a txt-file of the following format 
(1 row = 1 specimen). 
x1y1z1 x2y2z2 x3y3z3 x4y4z4 cs
x1y1z1 x2y2z2 x3y3z3 x4y4z4 cs
I am quite confident that I got the file format right since other programs of 
the IMP series work absolutely fine.  

I would really appreciate your help! 
Best regards, Stefan

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[MORPHMET] JOBS: Howard University - Comparative Anatomy and Neurobiology

2016-12-14 Thread Ken Hayes
Howard University
College of Arts & Sciences 
Department of Biology

Assistant Professor of Neurobiology (tenure track)
Assistant Professor of Anatomy (tenure track)

Description
The Department of Biology in the College of Arts and Sciences at Howard 
University invites applications for two tenure-track positions at the rank of 
Assistant Professor, one with specialization in neurobiology and the other in 
comparative vertebrate anatomy. We seek outstanding applicants with a 
demonstrated track record of excellence in research and teaching.

Qualifications
Successful candidates are expected to develop vigorous, extramurally funded 
research programs in their areas of expertise, actively participate in the 
Department's teaching and curriculum development at the undergraduate and 
graduate levels, and mentor undergraduate and graduate students.

Candidates must have:
* Earned doctorate in Biology or related field, with a specialization in 
neurobiology or comparative vertebrate anatomy from an accredited institution,
* Record of scholarship, teaching, and professional service commensurate with 
the rank of assistant professor,
* Effective communication and organizational skills, and
* Postdoctoral and grant-writing experience preferred.

Application Process
Complete applications consist of a single PDF file containing 
1) a cover letter addressing qualifications listed above, 
2) a current curriculum vitae, 
3) a two-page statement of research accomplishments, interests, and future 
plans, 
4) a two-page statement of teaching experience and philosophy, and 
5) the names and contact information for at least three references who will 
provide letters upon request from the search committee. 

Completed applications should be addressed to the Chair of the search committee 
Dr. Franklin Ampy and emailed to either:

hubio.ne...@gmail.com for the neurobiology position 

hubio.a...@gmail.com for the comparative anatomy position. 

All application materials should be received by February 1, 2017 when screening 
will begin and continue until the positions are filled. 
The starting date for both positions is August 15, 2017. 
Additional details and information can be found at 
http://hubiosearch.wixsite.com/2017.

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[MORPHMET] Small object (insectivorous bat) photogrammetry

2016-12-14 Thread Giada Giacomini
Hi all,

I am quite new to photogrammetry and geometric morphometric worlds and I got a 
bit stocked. 
I am trying to build 3D models of insectivorous bat skulls employing 
photogrammetry (more details at the end) and Agisoft Photoscan software.
The methodology works quite well with bigger specimens (19 mm x 12 mm x 7 mm).
But with a smaller ones (e.g. 13 x 8 x 5 mm) the software has different 
problems in the 3D reconstruction: usually it is not able to reconstruct the 
dense cloud (doing “inside out” or providing a long scratch of points) or, if 
the first step had worked successfully, it isn’t able to align the 3 chunks 
together. 

The pictures are in focus and the specimens in the picture results big enough I 
would say.
We are trying with other software different from Agisoft but the reconstruction 
is still difficult.

Anyone of you have already tried to perform photogrammetry on such small 
objects? 
Do you have any suggestions or comments?

Many thanks

Giada

Photogrammetry equipment and camera settings:
Camera: NIKON D5300 (24 megapixel)
Lens: NIKON macro 60 mm, f2.8
Settings: 
4-5 cm from the specimen
100 ISO
f/32
0.5 sec exposure time 
No flash. 3 white lights
Focus: automatic focus on a manual selected square

-- 
MORPHMET may be accessed via its webpage at http://www.morphometrics.org
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RE: [MORPHMET] allometry adjustment in R

2016-12-14 Thread Adams, Dean [EEOBS]
Jin Yung,

Evaluating Rsq for multivariate data can be a bit tricky, as our intuition 
tends to gravitate to ‘what is a large Rsq’ and ‘what is a small Rsq’ in the 
univariate context.  To interpret the importance of a model effect in 
multivariate models, I much prefer a formal effect size.

We (Collyer, Sekora and Adams 2015: Heredity) described a Z-score approach for 
helping one intuit the strength of a model effect. If the Z-score for a 
particular term in the model is large, then there is a large effect on the 
patterns in the data, implying it is important to interpret biologically.  
Examples in the Collyer et al paper show their use for anova models (a related 
method is found in Adams and Collyer 2016).

In your case, I suggest that you first evaluate the Z-score for the interaction 
term, rather than its Rsq, to determine whether this statistically significant 
interaction is also biologically important. These are provided in the 
Procrustes ANOVA tables in geomorph (see help file).

Dean

Dr. Dean C. Adams
Professor
Department of Ecology, Evolution, and Organismal Biology
   Department of Statistics
Iowa State University
www.public.iastate.edu/~dcadams/
phone: 515-294-3834

From: Wong Jin Yung [mailto:wongjiny...@gmail.com]
Sent: Tuesday, December 13, 2016 9:54 PM
To: Adams, Dean [EEOBS] 
Cc: MORPHMET 
Subject: Re: [MORPHMET] allometry adjustment in R

Dear Dean,
Thank you for pointing out my conceptual mistake and explaining it in a way 
easy to understand. For my data, I think the interaction is not biologically 
meaningful, so I do not intend to further investigate the difference in 
allometric trajectories.

Following discussion is for everyone, I will elaborate more and see if people 
here are interested on my specific case -- maybe my case could help other 
students like me too: I have two groups, A & B. A has strong allometry but B 
does not (I tried running regression of shape~size on A & B separately, B gave 
insignificant result and low Rsq -- which is the reason why I have no interest 
on difference in allometric trajectories). But when I ran the regression on the 
full dataset with shape~size*group, I got significant size:group term with low 
Rsq (0.03) and significant HOS test with large angle. Shape prediction from 
common slope (with a simple shape~size on full dataset) did not account for the 
true allometric changes of group A (from separate shape~size for A) like what 
Dean said but did captured most of it, and is off for group B (but then group B 
has little & non-significant allometric changes...). Any further opinion will 
be appreciated, many thanks.

Best,
Jin Yung

On Tue, Dec 13, 2016 at 10:28 PM, Adams, Dean [EEOBS] 
mailto:dcad...@iastate.edu>> wrote:
Jin Yung,

Before sorting out an R-code equivalent for what MorphoJ does, I recommend that 
you revisit and re-read the last few posts on Morphmet concerning statistical 
and biological significance of comparisons of slopes.  The important thing to 
determine first and foremost is whether or not the significant interaction term 
in your model is biologically meaningful (ie, does it represent the underlying 
patterns in the data or is it spurious for some reason). If it does represent 
the underlying patterns in  your data, than any pooled-group or common 
regression-based allometric residuals makes no sense.

Think of it this way: both a common slope model and a pooled within-group model 
assume that patterns of within-group covariation are equivalent (‘the same’ in 
vernacular speech).  If that assumption can be made, then one can fit a common 
slope or pooled-within group model and obtain so-called allometry-free 
residuals.  However, if the groups really do have different slopes, that means 
the within-group allometric trajectories are different. In this case it makes 
no sense to obtain allometric residuals from a common slope model, or a 
pooled-within group model, as these models do not account for the different 
shape~size relationships in each group. Thus, the common-slope analysis is not 
accounting for the actual allometric patterns in any of the groups. What that 
means is that the residuals for group A are not residuals from the shape~size 
allometric relationship in group A, but rather are the allometric residuals of 
this group +/- the difference in that groups’ slope versus the common-slope 
model. And likewise for group B, group C, etc.   Importantly, note that the 
difference in actual within-group residuals from common-slope residuals is not 
a constant across groups: meaning that there is no way to make these residuals 
comparable units for downstream analyses.

Additionally, obtaining residuals from a separate slopes model (i.e., a model 
containing the interaction term, as you have in your post) also makes little 
sense because here the residuals are obtained from different allometric 
trajectories for each group.  Thus, those residuals are not comparable,