Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Pelacakan objek dapat melacak beberapa objek yang terdeteksi dalam video input atau segmen
video dan menampilkan
label (tag) yang terkait dengan entitas yang terdeteksi beserta lokasi entitas dalam
frame.
Pelacakan objek berbeda dengan
deteksi label. Meskipun deteksi
label memberikan label untuk seluruh frame (tanpa kotak pembatas),
pelacakan objek mendeteksi setiap objek dan memberikan label beserta
kotak pembatas yang menjelaskan lokasi dalam frame untuk setiap objek. Misalnya, video
kendaraan yang melintasi persimpangan dapat menghasilkan label seperti "mobil", "truk",
"sepeda", "ban", "lampu", "jendela", dan sebagainya. Setiap label menyertakan serangkaian kotak pembatas yang menunjukkan lokasi objek dalam frame.
Setiap kotak pembatas juga memiliki segmen waktu terkait
dengan offset waktu (stempel waktu) yang menunjukkan offset durasi dari
awal video. Anotasi juga berisi informasi entity tambahan
termasuk ID entity yang dapat Anda gunakan untuk menemukan informasi lebih lanjut
tentang entity tersebut di
Google Knowledge Graph Search API.
Untuk membuat permintaan pelacakan objek, panggil metode annotate dan tentukan OBJECT_TRACKING di kolom features.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-17 UTC."],[],[],null,["# Object tracking\n\n*Object tracking* can track multiple objects detected in an input video or video\nsegments and return\nlabels (tags) associated with the detected entities along with the location of the entity in\nthe frame.\n| **Note:** There is a limit on the size of the detected objects. Very small objects in the video might not get detected.\n\nObject tracking differs from\n[label detection](/video-intelligence/docs/analyze-labels). While label\ndetection provides labels for the entire frame (without bounding boxes),\nobject tracking detects individual objects and provides a label along with\na bounding box that describes the location in the frame for each object. For example, a video\nof vehicles crossing an intersection may produce labels such as \"car\" , \"truck\",\n\"bike\", \"tires\", \"lights\", \"window\" and so on. Each label includes a series\nof bounding boxes showing the location of the object in the frame.\nEach bounding box also has an associated time segment\nwith a time offset (timestamp) that indicates the duration offset from\nthe beginning of the video. The annotation also contains additional entity\ninformation including an entity id that you can use to find more information\nabout that entity in the\n[Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).\n\nTo make an object tracking request, call the\n[`annotate`](/video-intelligence/docs/reference/rest/v1p2beta1/videos/annotate)\nmethod and specify\n[`OBJECT_TRACKING`](/video-intelligence/docs/reference/rest/v1p2beta1/videos#Feature)\nin the `features` field.\n\nCheck out the [Video Intelligence API visualizer](https://zackakil.github.io/video-intelligence-api-visualiser/#Object%20Tracking) to see this feature in action.\n\nFor an example, see [Object Tracking](/video-intelligence/docs/object-tracking)\nand [Shot Change Detection](/video-intelligence/docs/shot-detection) tutorial."]]
