Lights, Camera, Possibilities by https://padlet.com/k8clmn/pu050sj6i5cq Cameras and Wildlife Photo Identification en-us 2019-03-01 01:00:11 UTC 2025-11-06 06:11:15 UTC hello@padlet.com https://padlet-assets.s3.amazonaws.com/icons/Pictureland.png The Pros k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/336700009 With the advent of cell phone cameras, more and more wildlife photos are becoming available all over the world. Researchers have started to recruit citizen scientists to gather photos both at home or when abroad (Escobar et. al., 2018). 

The creation of systems such as Wildbook, were photos can be added to a digital library for identification. With the use of citizen scientists, researchers are capable of collecting more photos of individual animals and at a large scale across geographical locations. In fact, in 2016, 40,000 photographs were loaded into Wildbook via a collective effort between researchers, school children, tribal chiefs, and ambassadors in Kenya. These photos focused of Grevy's Zebra, whos numbers had counted on a small scale. Due to the large scale collaborative effort via Wildbook, the most accurate data of Grevy's Zebra's was collected and is now recognized on the IUCN Red List of Threatened Species (Reed, 2018). ]]> 2019-03-01 01:00:11 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/336700009 Population k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/336700011 Photo identification has enabled wildlife researches to assess population density and biodiversity. In a study by Debata and Swain (2018), researchers were able to determine the diversity and abundance of "naturally marked" (i.e. stripe, spot, or notching patterns) animals in eastern India. 

This brings up the question, what about animals, such as antelope, rhino, or other animals that lack natural markings? Well, with the development of new technologies and algorithms, identifying animals of every species (Timmins, 2019) is becoming a real possibility.  ]]> 2019-03-01 01:00:11 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/336700011 The Cons k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337230156 Taking photos and going through photos is a slow process and takes a lot of man/woman power. In order to have an accurate data library, many photos must be retrieved and accurately identified (Speed et. al., 2007). Additionally, relatively detailed photos must be taken to properly identify an individual (Escobar, 2018). ]]> 2019-03-03 14:56:14 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337230156 Facial Recognition k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337230173 One tool that researchers have researchers have started to develop and utilize for wildlife photo identification is facial recognition. 

Facial recognition is most commonly used to match and record identity of individuals, most commonly, people (Wick, 2018). However, recent developments may now help in illegal wildlife trafficking (Thomas, 2018) and the identification of individuals that do not have natural markings, such as elephants (Timmins, 2019). 

Most predominately, facial recognition has been used to identify trafficked chimpanzees by using the program ChimpFace using photos of chimpanzees from the social media of known or possible traffickers (Timmins, 2019). ]]> 2019-03-03 14:56:25 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337230173 Who, What, When, Where, Why, How? k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337296646 Identifying wildlife through photos has proven to be a relatively cheap, useful, and nonintrusive way to both track and identify various species (Brooks et. al., 2010). Scientists have utilized photographic information to determine population, species abundance, and to track individuals (Debata and Swain, 2018). The development of new technologies has also allowed for photos to be identified faster (Speed et. al., 2007)  and has utilized citizen science (Escobar et. al, 2018) to gather even more information than ever before! 


]]> 2019-03-03 23:52:57 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337296646 Identifying Individuals k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337299857 Scientists have been able to identify certain individuals through natural patterns on animals such as cheetahs, giraffe, orca, whale sharks, etc. The benefit to this is that an individual animal can then be tracked via a photo library that can be accessed over the corse of that individuals life (Speed et. al., 2007).

However, when making photo identification, quality is key. Smaller animals require a certain lens for accurate identification (Escobar et. al., 2018). ]]> 2019-03-04 00:20:33 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337299857 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313324 2019-03-04 01:46:42 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313324 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313578 Photo retrieved from: Retrieved from: https://www.bbc.com/news/science-environment-46945302. 3/3/19.]]> 2019-03-04 01:48:01 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313578 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313629 Wildbook: Our Vision in One Minute by Wild Me. Retrieved from: https://travelconserve.wordpress.com/2019/03/03/listen-up-and-conserve/. 3/3/19. ]]> 2019-03-04 01:48:22 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313629 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313682 Photo retrieved from: https://sciencenode.org/feature/Wildbook.phphttps://sciencenode.org/feature/Wildbook.php. 3/3/19.]]> 2019-03-04 01:48:40 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337313682 Faster, Faster! k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337320472 Now that millions, upon millions, of photos are capable of being uploaded to digital photo databases by literally anyone, who is going to go through all those photos? 

There in lays the beauty of new technological development. Algorithms have been created to go through photos at lightning speed. In one instance, a algorithm was developed and processed 375,000 images at 2,000 images a minute with 97.6% accuracy (Sandle, 2018). 

More photos means more data available to researchers. This algorithms allow researchers to determine species, number of animals, and what the animals are up to (Furness, 2018). ]]> 2019-03-04 02:31:44 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337320472 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337320802 2019-03-04 02:34:14 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337320802 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337320847 Photo retrieved from: https://www.asmag.com/showpost/25402.aspx. 3/3/2019. ]]> 2019-03-04 02:34:33 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337320847 How accessible is this information? k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337324869 As technology becomes more readily available to everyone, so does the data that has been added to various databases. While being a valuable tool to researchers, the availability of an individual animals location and the time of which the photo was taken is also valuable to poachers (Reed, 2018). 

Luckily, measures are being taken to protect animal identities. In fact, Wildbook has partnered with a technology company to protect its information from falling into the wrong hands (Reed, 2019). ]]> 2019-03-04 03:01:29 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337324869 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337325118 2019-03-04 03:03:04 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337325118 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337325209 Citizens and scientists earn their stripes counting Kenya's zebras by Euronews Knowledge. Retrieved from: https://sciencenode.org/feature/Wildbook.phphttps://sciencenode.org/feature/Wildbook.php. 3/3/19.]]> 2019-03-04 03:03:38 UTC https://padlet.com/k8clmn/pu050sj6i5cq/wish/337325209 k8clmn https://padlet.com/k8clmn/pu050sj6i5cq/wish/337326700 Brooks, Katie, et. al. (2010). Seeing Spots: Photo-identification as a Regional Tool for Whale Shark Identification. Western Indian Ocean Journal, 9:2 185-194.

Debata, Subrat, and Swain, Kedra Kumar. (2018). Estimating mammalian diversity and relative abundance using camera traps in a tropical deciduous forest of Kuldiha Wildlife Sanctuary, eastern India. The Mammal Society of Japan, 43: 45-53. 

Escobar, Javier, et. al. (2018). Telescoping turtles: a comparison of smartphone telephoto magnifiers to non-invasively observe and identify freshwater turtles. Herpetological Journal, 28: 143-147.

Furness, Dyllan. (2018). One fish, two fish: A.I. labels wildlife photos to boost conservation. Digitaltrends.com. Retrieved from: https://www.digitaltrends.com/cool-tech/ai-animal-photograph/.

Reed, Laura. (2018). Combating extinction one photo at a time. Sciencenode.org. Retrieved from: https://sciencenode.org/feature/Wildbook.php.

Sandle, Tim. (2018). Using AI to identify animals from photos. Digitaljournal.com. Retrieved from: http://www.digitaljournal.com/news/environment/using-ai-to-identify-animals-from-photos/article/538150.

Speed, Conrad W, et. al. (2007). Spot the match - wildlife photo-identification using information theory. Frontiers in Zoology, 4:2.

Timmins, Beth. (2019). Facial recognition tool tackles illegal chimp trade. BBC.com. Retrieved from: https://www.bbc.com/news/science-environment-46945302.

Thomas, Prasanth Aby. (2018). Beyond humans: how facial recognition helps in wildlife preservation. Asmag.com. Retrieved from: https://www.asmag.com/showpost/25402.aspx.

Wick, Don. (2018). Visage Quest: The use of facial recognition software in law enforcement has benefits and drawbacks. Sheriff & Deputy, Pp. 78-79. 
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