@nastasiadelinee: BANDUNG EMNG LUCU LUCU SIH ISINYA 😭🫶🏻✨ gacukup sejam cobain photobooth di Braga :’) @xccurate #vlogkecil #haul #photobooth #challenge

Nastasia Adeline

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Friday 13 March 2026 13:51:27 GMT

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Comments

Dyland Maximus Zidane :

Lucu banget partner ini

2026-03-13 21:11:06

5851

Nad. :

SERIUS INI MEREKA GAK PACARAN?!!

2026-03-13 14:45:01

9496

serenite🌙 :

"partner kerja"

2026-03-13 18:56:49

2615

Neel.Gard :

lucu amat, jangan slek dulu ya

2026-03-13 13:55:35

2234

mugenn :

2026-03-13 13:55:51

277

kia :

my fav couple acu🤏🏻

2026-03-13 13:57:41

76

BKRSTR :

KALO ADA SERIBU PERCAYA INI PARTNER KERJA GW SALAH SATUNYA

2026-03-13 15:20:41

614

Kita Konser :

PEMINAT NO 1 PERKEDELLL

2026-03-13 14:46:01

18

Screamlinee :

partner kerjanya ngepartner banget

2026-03-13 14:39:14

106

a :

duniaa gue bangett 😭😭😭

2026-04-19 16:05:41

7

⃟ :

couple ini lagi

2026-03-16 11:48:10

5

Fadel Yuda :

beb??

2026-03-13 16:29:23

8

awa :

IH KNP GA COBA DI PHOTOMATIC🫠🫠

2026-03-31 23:42:57

19

uli :

otw jadi couple hitz tiktok cheekkkk 😎📸

2026-03-13 14:00:38

122

🍓🫰🏻 :

couple fav acu gemes bangettt😭😻💖

2026-03-13 16:38:35

9

canduu :

Murah murah bngt ci klo di kaltim paling murah 70 rbuan😭

2026-03-13 22:21:46

128

funata_1 :

😚😚 lucu bgtttt

2026-03-13 14:03:14

10

Bell Embun. :

2026-03-14 05:18:01

13

lyfafter24 :

couple tiktok favorit aing nih bous

2026-03-13 17:01:11

9

strawberry🧃 :

kalian aja yang ngomong gw udah cape

2026-03-13 15:30:12

15

thoinksomnea :

BHAPPP sangat temen KERJAAAA🥰

2026-03-14 00:02:13

8

ciwww :

KOK LUCU 🥺

2026-03-13 14:01:10

7

Clx :

2026-03-13 14:24:02

30

To see more videos from user @nastasiadelinee, please go to the Tikwm homepage.

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Video compression is the process of reducing the file size of a video so it can be streamed easily over the internet. Raw video files are massive because they contain up to sixty full-color images for every single second of footage. To shrink this data compression algorithms exploit two types of redundancy known as spatial and temporal. Spatial compression looks for redundancy within a single individual frame of the video. If a frame shows a clear blue sky the algorithm does not save the color data for every single pixel. Instead it groups those pixels together and records a single instruction to fill that entire area with blue. This process is highly efficient for static backgrounds and works similarly to how a JPEG image is compressed. Temporal compression looks for redundancy across multiple sequential frames over a period of time. In most video scenes very little actually changes from one frame to the next millisecond. If a person is walking in front of a house the house stays completely still while only the person moves. Instead of saving a whole new picture for the next frame the algorithm only records the differences or changes. It saves the moving parts as motion vectors and instructs the player to reuse the static background from the previous frame. The algorithm organizes these frames into a structure called a Group of Pictures which includes I-frames P-frames and B-frames. I-frames are full images that contain all the spatial data needed to render a complete picture without any outside context. P-frames and B-frames are smaller predictive frames that only contain the temporal data of what changed since the last frame. Combining spatial and temporal compression allows platforms to shrink video file sizes by over ninety-five percent without a noticeable loss in quality.

Video compression is the process of reducing the file size of a video so it can be streamed easily over the internet. Raw video files are massive because they contain up to sixty full-color images for every single second of footage. To shrink this data compression algorithms exploit two types of redundancy known as spatial and temporal. Spatial compression looks for redundancy within a single individual frame of the video. If a frame shows a clear blue sky the algorithm does not save the color data for every single pixel. Instead it groups those pixels together and records a single instruction to fill that entire area with blue. This process is highly efficient for static backgrounds and works similarly to how a JPEG image is compressed. Temporal compression looks for redundancy across multiple sequential frames over a period of time. In most video scenes very little actually changes from one frame to the next millisecond. If a person is walking in front of a house the house stays completely still while only the person moves. Instead of saving a whole new picture for the next frame the algorithm only records the differences or changes. It saves the moving parts as motion vectors and instructs the player to reuse the static background from the previous frame. The algorithm organizes these frames into a structure called a Group of Pictures which includes I-frames P-frames and B-frames. I-frames are full images that contain all the spatial data needed to render a complete picture without any outside context. P-frames and B-frames are smaller predictive frames that only contain the temporal data of what changed since the last frame. Combining spatial and temporal compression allows platforms to shrink video file sizes by over ninety-five percent without a noticeable loss in quality.

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